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  Subjects -> HUMANITIES (Total: 987 journals)
    - ASIAN STUDIES (167 journals)
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    - HUMANITIES (315 journals)
    - NATIVE AMERICAN STUDIES (28 journals)

HUMANITIES (315 journals)                  1 2     

Showing 1 - 71 of 71 Journals sorted alphabetically
Aboriginal and Islander Health Worker Journal     Full-text available via subscription   (Followers: 15)
Aboriginal Child at School     Full-text available via subscription   (Followers: 6)
About Performance     Full-text available via subscription   (Followers: 13)
Access     Full-text available via subscription   (Followers: 26)
ACCESS: Critical Perspectives on Communication, Cultural & Policy Studies     Full-text available via subscription   (Followers: 12)
Acta Academica     Full-text available via subscription   (Followers: 6)
Acta Universitaria     Open Access   (Followers: 7)
Adeptus     Open Access   (Followers: 1)
Advocate: Newsletter of the National Tertiary Education Union     Full-text available via subscription   (Followers: 1)
Afghanistan     Hybrid Journal   (Followers: 1)
African and Black Diaspora: An International Journal     Hybrid Journal   (Followers: 19)
African Historical Review     Hybrid Journal   (Followers: 17)
AFRREV IJAH : An International Journal of Arts and Humanities     Open Access   (Followers: 6)
Agriculture and Human Values     Open Access   (Followers: 15)
Akademika : Journal of Southeast Asia Social Sciences and Humanities     Open Access   (Followers: 6)
Alterstice : Revue internationale de la recherche interculturelle     Open Access  
Altre Modernità     Open Access   (Followers: 3)
Amaltea. Revista de mitocrítica     Open Access   (Followers: 1)
American Imago     Full-text available via subscription   (Followers: 3)
American Journal of Humanities and Social Sciences     Open Access   (Followers: 12)
American Review of Canadian Studies     Hybrid Journal   (Followers: 6)
Anabases     Open Access   (Followers: 2)
Analyse & Kritik. Zeitschrift für Sozialtheorie     Hybrid Journal   (Followers: 1)
Angelaki: Journal of Theoretical Humanities     Hybrid Journal   (Followers: 19)
Anglo-Saxon England     Hybrid Journal   (Followers: 36)
Antik Tanulmányok     Full-text available via subscription  
Antipode     Hybrid Journal   (Followers: 57)
Anuario Americanista Europeo     Open Access  
Arbutus Review     Open Access   (Followers: 1)
Argumentation et analyse du discours     Open Access   (Followers: 7)
Ars & Humanitas     Open Access   (Followers: 14)
Artefact : Techniques, histoire et sciences humaines     Open Access  
Artes Humanae     Open Access  
Arts and Humanities in Higher Education     Hybrid Journal   (Followers: 39)
Asia Europe Journal     Hybrid Journal   (Followers: 4)
Australasian Journal of Popular Culture, The     Hybrid Journal   (Followers: 2)
Behaviour & Information Technology     Hybrid Journal   (Followers: 52)
Behemoth     Open Access   (Followers: 3)
Belin Lecture Series     Open Access   (Followers: 1)
Bereavement Care     Hybrid Journal   (Followers: 12)
Bulletin of the School of Oriental and African Studies     Hybrid Journal   (Followers: 21)
Cahiers de praxématique     Open Access   (Followers: 1)
Cankiri Karatekin University Journal of Faculty of Letters     Open Access  
Child Care     Full-text available via subscription   (Followers: 6)
Chinese Studies Journal     Open Access  
Chronicle of Philanthropy     Full-text available via subscription   (Followers: 3)
Ciencias Sociales y Humanidades     Open Access   (Followers: 4)
Claroscuro     Open Access   (Followers: 1)
Coaching: An International Journal of Theory, Research and Practice     Hybrid Journal   (Followers: 10)
Cogent Arts & Humanities     Open Access   (Followers: 3)
Colloquia Humanistica     Open Access  
Communication and Critical/Cultural Studies     Hybrid Journal   (Followers: 29)
Comprehensive Therapy     Hybrid Journal   (Followers: 3)
Con Texte     Open Access  
Congenital Anomalies     Hybrid Journal   (Followers: 1)
Conjunctions. Transdisciplinary Journal of Cultural Participation     Open Access   (Followers: 4)
Conservation Science in Cultural Heritage     Open Access   (Followers: 10)
Creative Industries Journal     Hybrid Journal   (Followers: 8)
Critical Arts : South-North Cultural and Media Studies     Hybrid Journal   (Followers: 12)
Crossing the Border : International Journal of Interdisciplinary Studies     Open Access   (Followers: 6)
Cuadernos de historia de España     Open Access   (Followers: 4)
Cuadernos de la Facultad de Humanidades y Ciencias Sociales. Universidad Nacional de Jujuy     Open Access  
Cultural History     Hybrid Journal   (Followers: 27)
Cultural Studies     Hybrid Journal   (Followers: 58)
Culturas : Debates y Perspectivas de un Mundo en Cambio     Open Access   (Followers: 1)
Culture, Theory and Critique     Hybrid Journal   (Followers: 29)
Daedalus     Hybrid Journal   (Followers: 24)
Dandelion : Postgraduate Arts Journal & Research Network     Open Access   (Followers: 4)
Death Studies     Hybrid Journal   (Followers: 19)
Digital Humanities Quarterly     Open Access   (Followers: 56)
Digital Studies / Le champ numerique     Open Access  
Digitális Bölcsészet / Digital Humanities     Open Access  
Diogenes     Hybrid Journal   (Followers: 8)
Doct-Us Journal     Open Access  
Dokuz Eylül Üniversitesi Edebiyat Fakültesi Dergisi / Dokuz Eylül University Journal of Humanities     Open Access  
Dorsal : Revista de Estudios Foucaultianos     Open Access  
E+E : Estudios de Extensión en Humanidades     Open Access  
e-Hum : Revista das Áreas de Humanidade do Centro Universitário de Belo Horizonte     Open Access   (Followers: 2)
Early Modern Culture Online     Open Access   (Followers: 36)
EAU Heritage Journal Social Science and Humanities     Open Access  
Égypte - Monde arabe     Open Access   (Followers: 6)
Eighteenth-Century Fiction     Full-text available via subscription   (Followers: 18)
Éire-Ireland     Full-text available via subscription   (Followers: 9)
En-Claves del pensamiento     Open Access   (Followers: 1)
Enfoques     Open Access  
Ethiopian Journal of the Social Sciences and Humanities     Full-text available via subscription   (Followers: 8)
Études arméniennes contemporaines     Open Access   (Followers: 3)
Études canadiennes / Canadian Studies     Open Access   (Followers: 2)
Études de lettres     Open Access   (Followers: 3)
European Journal of Cultural Studies     Hybrid Journal   (Followers: 30)
European Journal of Social Theory     Hybrid Journal   (Followers: 21)
Expositions     Full-text available via subscription  
Fa Nuea Journal     Open Access  
Fields: Journal of Huddersfield Student Research     Open Access  
Fronteras : Revista de Ciencias Sociales y Humanidades     Open Access   (Followers: 2)
Frontiers in Digital Humanities     Open Access   (Followers: 5)
Fudan Journal of the Humanities and Social Sciences     Hybrid Journal  
GAIA - Ecological Perspectives for Science and Society     Full-text available via subscription   (Followers: 2)
German Research     Hybrid Journal   (Followers: 1)
German Studies Review     Full-text available via subscription   (Followers: 28)
Germanic Review, The     Hybrid Journal   (Followers: 6)
Globalizations     Hybrid Journal   (Followers: 9)
Gruppendynamik und Organisationsberatung     Hybrid Journal   (Followers: 2)
Habitat International     Hybrid Journal   (Followers: 7)
Hacettepe Üniversitesi Edebiyat Fakültesi Dergisi     Open Access   (Followers: 2)
Harvard Journal of Asiatic Studies     Full-text available via subscription   (Followers: 13)
Heritage & Society     Hybrid Journal   (Followers: 16)
History of Humanities     Full-text available via subscription   (Followers: 8)
Hopscotch: A Cultural Review     Full-text available via subscription   (Followers: 1)
Human Affairs     Hybrid Journal   (Followers: 1)
Human and Ecological Risk Assessment: An International Journal     Hybrid Journal   (Followers: 4)
Human Nature     Hybrid Journal   (Followers: 22)
Human Performance     Hybrid Journal   (Followers: 9)
Human Remains and Violence : An Interdisciplinary Journal     Full-text available via subscription  
Human Studies     Hybrid Journal   (Followers: 9)
humanidades     Open Access  
Humanitaire     Open Access   (Followers: 2)
Humanities     Open Access   (Followers: 15)
Humanities and Social Sciences     Open Access  
Humanities and Social Sciences Journal of Graduate School, Pibulsongkram Rajabhat University     Open Access  
Humanities and Social Sciences Journal, Ubon Ratchathani Rajabhat University     Open Access  
Humanities Diliman : A Philippine Journal of Humanities     Open Access  
Humanities, Arts and Social Sciences Studies (HASSS)     Open Access  
Hungarian Cultural Studies     Open Access  
Hungarian Studies     Full-text available via subscription  
Ibadan Journal of Humanistic Studies     Full-text available via subscription  
Inkanyiso : Journal of Humanities and Social Sciences     Open Access   (Followers: 1)
Insaniyat : Journal of Islam and Humanities     Open Access   (Followers: 1)
Inter Faculty     Open Access  
Interim : Interdisciplinary Journal     Open Access   (Followers: 4)
International Journal for History, Culture and Modernity     Open Access   (Followers: 9)
International Journal of Arab Culture, Management and Sustainable Development     Hybrid Journal   (Followers: 7)
International Journal of Cultural Studies     Hybrid Journal   (Followers: 30)
International Journal of Heritage Studies     Hybrid Journal   (Followers: 17)
International Journal of Humanities and Arts Computing     Hybrid Journal   (Followers: 13)
International Journal of Humanities and Cultural Studies     Open Access   (Followers: 11)
International Journal of Humanities of the Islamic Republic of Iran     Open Access   (Followers: 10)
International Journal of Humanity Studies     Open Access  
International Journal of Listening     Hybrid Journal   (Followers: 3)
International Journal of the Classical Tradition     Hybrid Journal   (Followers: 13)
Interventions : International Journal of Postcolonial Studies     Hybrid Journal   (Followers: 18)
ÍSTMICA. Revista de la Facultad de Filosofía y Letras     Open Access   (Followers: 1)
Jangwa Pana     Open Access  
Jednak Książki : Gdańskie Czasopismo Humanistyczne     Open Access  
Jewish Culture and History     Hybrid Journal   (Followers: 19)
Journal de la Société des Américanistes     Open Access  
Journal des africanistes     Open Access   (Followers: 1)
Journal des Economistes et des Etudes Humaines     Hybrid Journal  
Journal for Cultural Research     Hybrid Journal   (Followers: 12)
Journal for General Philosophy of Science     Hybrid Journal   (Followers: 7)
Journal for Learning Through the Arts     Open Access   (Followers: 7)
Journal for New Generation Sciences     Open Access   (Followers: 4)
Journal for Research into Freemasonry and Fraternalism     Hybrid Journal  
Journal for Semitics     Full-text available via subscription   (Followers: 8)
Journal Of Advances In Humanities     Open Access   (Followers: 3)
Journal of Aesthetics & Culture     Open Access   (Followers: 23)
Journal of African American Studies     Hybrid Journal   (Followers: 11)
Journal of African Cultural Studies     Hybrid Journal   (Followers: 5)
Journal of African Elections     Full-text available via subscription  
Journal of Arts & Communities     Hybrid Journal   (Followers: 6)
Journal of Arts and Humanities     Open Access   (Followers: 24)
Journal of Arts and Social Sciences     Open Access  
Journal of Bioethical Inquiry     Hybrid Journal   (Followers: 3)
Journal of Burirum Rajabhat University     Open Access  
Journal of Cultural Economy     Hybrid Journal   (Followers: 9)
Journal of Cultural Geography     Hybrid Journal   (Followers: 21)
Journal of Data Mining and Digital Humanities     Open Access   (Followers: 40)
Journal of Developing Societies     Hybrid Journal   (Followers: 1)
Journal of Family Theory & Review     Hybrid Journal   (Followers: 3)
Journal of Franco-Irish Studies     Open Access   (Followers: 1)
Journal of Happiness Studies     Hybrid Journal   (Followers: 28)
Journal of Humanities and Social Sciences     Open Access  
Journal of Humanities and Social Sciences Surin Rajabhat University     Open Access  
Journal of Humanities and Social Sciences, Rajapruk University     Open Access  
Journal of Interactive Humanities     Open Access   (Followers: 3)
Journal of Intercultural Communication Research     Hybrid Journal   (Followers: 15)
Journal of Intercultural Studies     Hybrid Journal   (Followers: 12)
Journal of Interdisciplinary History     Hybrid Journal   (Followers: 22)
Journal of Labor Research     Hybrid Journal   (Followers: 20)
Journal of Medical Humanities     Hybrid Journal   (Followers: 22)
Journal of Medieval and Early Modern Studies     Full-text available via subscription   (Followers: 38)
Journal of Modern Greek Studies     Full-text available via subscription   (Followers: 4)
Journal of Modern Jewish Studies     Hybrid Journal   (Followers: 14)
Journal of Open Humanities Data     Open Access   (Followers: 2)
Journal of Semantics     Hybrid Journal   (Followers: 15)
Journal of the Musical Arts in Africa     Hybrid Journal   (Followers: 1)
Journal of University of Babylon for Humanities     Open Access  
Journal of Visual Culture     Hybrid Journal   (Followers: 33)
Journal Sampurasun : Interdisciplinary Studies for Cultural Heritage     Open Access   (Followers: 1)
Jurisprudence     Hybrid Journal   (Followers: 18)
Jurnal Ilmu Sosial dan Humaniora     Open Access  
Jurnal Pendidikan Humaniora : Journal of Humanities Education     Open Access   (Followers: 1)
Jurnal Sosial Humaniora     Open Access   (Followers: 2)
L'Orientation scolaire et professionnelle     Open Access   (Followers: 1)
La lettre du Collège de France     Open Access   (Followers: 1)
Lagos Notes and Records     Full-text available via subscription  
Language and Intercultural Communication     Hybrid Journal   (Followers: 23)
Language Resources and Evaluation     Hybrid Journal   (Followers: 5)
Law and Humanities     Hybrid Journal   (Followers: 7)
Law, Culture and the Humanities     Hybrid Journal   (Followers: 12)

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Similar Journals
Journal Cover
Journal Prestige (SJR): 0.733
Citation Impact (citeScore): 3
Number of Followers: 3  
  Hybrid Journal Hybrid journal (It can contain Open Access articles)
ISSN (Print) 0263-2241
Published by Elsevier Homepage  [3184 journals]
  • Enhanced temperature stability of scale factor in MEMS gyroscope based on
           multi parameters fusion compensation method
    • Abstract: Publication date: December 2019Source: Measurement, Volume 148Author(s): Jian Cui, Guizhen Yan, Qiancheng ZhaoAbstractScale factor thermal sensitivity is an essential performance index of microelectromechanical system (MEMS) gyroscopes and is typically used to characterize the temperature stability of inertial sensors. This study demonstrates a novel compensation method to enhance the temperature stability of the scale factor for an amplitude-modulated (AM) MEMS gyroscope operating in split-mode based on multiparameter fusion compensation (MPFC). A mathematical model for the temperature sensitivity of the scale factor is established, which indicates that the resonant frequency of the primary mode, voltage amplitude of the primary mode displacement, frequency split of the two working modes, and demodulation phase error are the decisive factors that affect the thermal sensitivity of the scale factor. The temperature performance of the scale factor can be significantly improved with MPFC by a weighted linear combination of the four factors. The results show that the temperature sensitivity of the scale factor decreases from 370 to 33 ppm/°C over the temperature range of −30 to 70 °C, representing a reduction by an order of magnitude. The thermal sensitivity of the scale factor can be further reduced to approximately 8 ppm/°C by applying the proposed compensation technique after increasing the stability of the demodulation phase error.
  • Computer-aided cancer classification system using a hybrid level-set image
    • Abstract: Publication date: December 2019Source: Measurement, Volume 148Author(s): Abdulaziz Alarifi, Ayed AlwadainAbstractIn computer vision, image segmentation plays an indispensable role. Image segmentation is used to find objects and their boundary limits in images. In medical imaging, tasks such as finding pathological regions and automatic detection of diseases are a complicated problem for computer science and image processing. This problem is intricate because of insufficient clarity of images. High segmentation accuracy, efficiency, reliability, and ability to handle noise or inhomogeneous intensity are some of the desired characteristics of a good segmentation algorithm for medical images. This study proposes an automatic computer-aided system that has been developed by using a level-set region-based active contour segmentation algorithm for edge detection of 2D medical images with and without inhomogeneous intensity. In this method, cancer images are segmented in the transformed domain, which helps to reduce the noise. The proposed segmentation algorithm combines the local geometric properties and local image fitting properties to correctly identify the pixels corresponding to different regions, in images with or without intensity inhomogeneity. The performance of the proposed method is analyzed with panoramic radiograph, Matrix Laboratory. In the experiments, the proposed method outperforms the baselines.
  • Novel method of measuring optical freeform surface based on laser focusing
           probe without calibrating focus error signal
    • Abstract: Publication date: December 2019Source: Measurement, Volume 148Author(s): Yiting Duan, Quangsang Vo, Xiaodong Zhang, Yingmo Wang, Siyu Huang, Fengzhou FangAbstractA new method was developed for measuring an optical freeform surface with a noncontact laser focusing probe. The measurement process does not require calibration of the focus error signal (FES). Without the calibration process when measuring the workpiece topography greatly increases the measurement efficiency compared to the traditional astigmatism method, which extends the measurement range while providing high accuracy and stability. The new method was used to design a low-cost, noncontact, high-accuracy, and autofocusing laser probe. A dynamic focusing scheme was designed for measurement control software that can eliminate environmental interference and other noise to achieve fast and accurate focusing. Experimental results for a 10 µm standard step height verified the accuracy of the developed measurement system with an average error of 0.0141 µm, root mean squared error of 0.0432 µm, and standard deviation of 0.0201 µm. The developed system can be applied to measuring the optical freeform surface of low-reflectivity materials.
  • Fiber optic array as an alternative to the optical lens in microscopy: A
           proof-of-concept study
    • Abstract: Publication date: December 2019Source: Measurement, Volume 148Author(s): Weiming Wang, Hang Liu, Fengyu Cong, Yan Yu, Aobo CuiAbstractThe majority of optical microscopes rely heavily on the lens group because of the low cost and ease of use. However, this type of microscope is limited by the relative long working distance, large chromatic aberration and complex structure. As an alternative to the lens, fiber optic array (FOA) can overcome the above limitations and achieve better results in the same magnification scale. This paper demonstrated that the microscope based on the FOA had a comparable resolution (3 μm) with the traditional lens group microscope, while the field-of-view (FOV) of FOA was almost four times larger than the latter. Without any manual focus, the volume and distortion of our FOA microscope were obviously smaller than that of the lens group microscope. To obtain a better microscopy imaging performance based on the FOA, the coupling efficiency and signal-to-noise ratio (SNR) of the FOA microscope were analyzed and some related measures for improvement were proposed.
  • Contour-oriented automatic tracking based on Gaussian processes for atomic
           force microscopy
    • Abstract: Publication date: December 2019Source: Measurement, Volume 148Author(s): Chengfei Yang, Wenting Wang, Yuhang ChenAbstractA local scan method based on Gaussian processes inference was developed for efficient atomic force microscopy measurements of string-like nano-objects such as DNA molecules, nanowires, shape boundaries, and so on. Unlike conventional line-by-line raster scan, the proposed method can adaptively track the nano-objects deposited on a flat substrate through accurate prediction of the x- and y- coordinates along the objective contour. Therefore, the used time in scanning the featureless substrate is drastically eliminated. Compared with conventional raster scan, the time efficiency can be improved by almost one order of magnitude. Numerical simulations and practical experiments demonstrated that such a method has several advantages including automatic tracking, significant reduction of scan distance and improvement of measurement efficiency.
  • Progressive Gaussian approximation filter with adaptive measurement update
    • Abstract: Publication date: December 2019Source: Measurement, Volume 148Author(s): Xusheng Yang, Cheng Zhao, Bo ChenAbstractThis paper presents a progressive Gaussian approximation filter with adaptive measurement update for nonlinear systems. First, a progressive Gaussian filtering (PGF) framework with variable step-size is presented by using the Bayesian rule, and second, a progressive Gaussian approximation filter is designed under the framework of the variable step-size PGF, where the means and covariances of corresponding Gaussian distributions are calculated by using the unscented transform. Moreover, termination conditions for stopping the progressive measurement update are given, which are not only good for the computational efficiency, but also improve the adaptive ability against measurement uncertainties. Finally, by simulations of a target tracking example, it demonstrates that the proposed method has higher computational efficiency and robustness than the existing PGAF.
  • Use of waste copper slag filled jute fiber reinforced composites for
           effective erosion prevention
    • Abstract: Publication date: December 2019Source: Measurement, Volume 148Author(s): G. Kalusuraman, S. Thirumalai Kumaran, M. Aslan, T. Küçükömeroğluc, I. SivaAbstractThis work addresses the erosion performance of waste copper slag filled jute fiber reinforced polyester composites. The composites are prepared by two different fiber treatment methods such as sodium hydroxide (NT) and calcium hydroxide (CT) and the results are compared with the specimen prepared by untreated fiber (UT). The fiber dosage of 40% and the waste copper slag filler materials of 10% are used to prepare the composites. A compression molding machine with an optimum pressure of 17 MPa is used for the fabrication process. Erosion tests are conducted on an erosion test rig by varying the input process parameters such as impingement angle (30°, 60°, 90°) and jet pressure (70, 100, 130 m/s). The experimental result shows that use of copper slag filler particles increased the interfacial bond between the matrix and fiber resulting to erosion prevention. A regression model has been developed for each composite to predict the future values. Further, the desirability analysis was performed and found that the CT composite with impingement angle at 90° and jet velocity at 86.36 m/s could achieve lower erosion rate. Finally, the erosion mechanism of the eroded surface of the composite has been studied using scanning electron microscope and 3D surface profilometry images.
  • Objective evaluation on yarn hairiness detection based on multi-view
           imaging and processing method
    • Abstract: Publication date: December 2019Source: Measurement, Volume 148Author(s): Wendi Wang, Binjie Xin, Na Deng, Jiaping LiAbstractIn this paper, a multi-view yarn image acquisition device was proposed to collect yarn images from many different viewing angles instead of a single viewing angle, for the purpose of obtaining the expected accurate measurement. One set of the proposed image processing algorithms, quite qualified for processing the multi-view yarn image sequences, was employed to obtain the shape of the yarn hairiness viewed from different angles. Both lengths and numbers of yarn hairiness from different viewing angles could be identified, and besides, the average value of these hairiness parameters could be calculated to determine the quality of yarn hairiness. Our experimental results show that the multi-view imaging and processing method could be used to avoid the maximum or minimum value of the detection results, with more comprehensive yarn hairiness parameter information. In addition, as the guidance for the subsequent processing on yarn products, the processing results obtained from multi-view imaging and processing algorithm are characterized by reproducible, convenient for further study of yarn hairiness. Combined with the existing image processing algorithms, the multi-view image acquisition device put forward in this paper could be adopted to form a complete yarn hairiness detection system, providing a favorable theoretical support for the future development of digital yarn quality evaluation system.
  • Body anthropometric measurements of Singaporean adult and elderly
    • Abstract: Publication date: December 2019Source: Measurement, Volume 148Author(s): Yu-Chi Lee, Chun-Hsien Chen, Ching-Hung LeeAbstractThe aims of this study were 1) to investigate the gender differences in Singaporean adult and elderly people; 2) to compare the anthropometric dimensions between adults and older people. Two hundred subjects (100 adults and 100 older people; each group consisted of 50 male and 50 female subjects) were recruited in this study. A collection of the 36 body dimensions selected from ISO 7250 was conducted. Subjects aged from 18 to 64 years old were recruited as the adult group. Subjects aged 65 or over were defined as elderly. All body dimensions were measured manually using digital calipers and measuring tapes. The t-test results showed that gender differences were found in both the adult and elderly subjects. Males have greater measurements than females in the majority of the 36 body dimensions, in both the adult or elderly groups. There were significant differences in anthropometric data between Singaporean adults and elderly people. The results indicated that adult subjects had larger body dimensions than elderly subjects in most of the measurements in both genders. Additionally, anthropometric measurement comparisons between Singaporean and populations from other countries are also discussed in this study under the adult and elderly groups. The findings and the anthropometric data from this study can be used for relevant consideration in the development of ergonomic products, equipment, and workstation design.
  • Investigation of nanostructured surface layer of severe shot peened AISI
           1045 steel via response surface methodology
    • Abstract: Publication date: December 2019Source: Measurement, Volume 148Author(s): Okan Unal, Erfan Maleki, Ibrahim Kocabas, Haluk Yilmaz, Fazil HusemShot peening (SP) and also severe shot peening (SSP) provide high level compressive residual stress on a certain thickness just beneath the surface. By exposing severe plastic deformation (SPD) via SSP, the nanocrystallization is formed without any chemical alteration and the structure is to be hardened by fully mechanized process. The difference among SP, SSP and repeening (RP) is only related with the selection of the input parameters. Most of the input parameters combination constructs the Almen intensity which is the most powerful condition to be made the decision on the final shot peening of real parts. AISI 1045 medium carbon steel is selected for the optimization of input parameters (shot size, peening duration and air pressure at constant coverage-100%) by investigating the output responses (residual stress, hardness) using response surface methodology. Optimum SP parameters are introduced by response optimizer and the model is verified by the confirmation tests.Graphical abstractGraphical abstract for this article
  • Desktop Vs Cloud Computing Software For 3D Measurement Of Building
           Façades: The Monastery Of San Martín Pinario
    • Abstract: Publication date: Available online 26 August 2019Source: MeasurementAuthor(s): Simón Peña-Villasenín, Mariluz Gil-Docampo, Juan Ortiz-SanzThis study employs Structure from Motion (SfM) to survey a historic building façade. Professional photogrammetric software (Agisoft PhotoScan and Pix4D) is compared with low-cost photogrammetric software (Autodesk Remake) to analyse the accuracy of these solutions and compare their possibilities and ease of use through a complete methodological process. Here, 3D modelling was tested on the façade of San Martín Pinario. The performance, operational usefulness, visual and geometric quality and accuracy are analysed. The results show that cloud computing software offers 3D models with visual quality and an accuracy similar to those obtained with desktop software, with a minimum error in the tree cases of 0.5 cm and maximum in PhotoScan of 3.5 cm and with a similar mean error in all cases around 1.6 cm. Cost savings and ease of use make photogrammetric cloud computing a great measurement tool for professionals who are not specialists in photogrammetry.Graphical abstractGraphical abstract for this article
  • Classification of alveolar bone density using 3-D deep convolutional
           neural network in the cone-beam CT images: A 6-month clinical study
    • Abstract: Publication date: December 2019Source: Measurement, Volume 148Author(s): Majid Memarian Sorkhabi, Maryam Saadat KhajehBackgroundComputer-based diagnoses are a crucial study in the medical image analyzing and machine learning technologies. The cone beam computed tomography (CBCT) modality provides three-dimensional bone models to extract an interactive treatment plan at relatively low radiation dose and cost. For the first time in this study, the evaluation of alveolar bone density was performed by a 3-D deep convolutional neural network (CNN) at the CBCT images. The trabecular pattern of the bone was recognized and classified.MethodThis study aimed to present a methodology which was implementing 3D voxel-wise feature evaluation within a convolutional neural network. We presented a three-dimensional CNN method that evaluated the alveolar bone density from CBCT volumetric data which could efficiently capture the trabecular pattern. In clinical trials, 207 surgery target areas of 83 patients have been selected. Clinical parameters were measured and evaluated during the surgery and a 6-month follow-up. These parameters were used to database labeling and evaluate the performance of the proposed technique.ResultsOur method achieved the average precision score of 84.63% and 95.20% in the hexagonal prism and the cylindrical voxel shapes respectively. Furthermore, the alveolar bone classification was performed in 76 ms. In comparison to the state-of-art approaches, the efficiency of the suggested algorithm was proved.ConclusionAn automatic classification can improve the proficiency and certainty of the radiologic evaluation. The outcome of this research may help the dentists in the implant treatment from diagnosis to surgery.Graphical abstractGraphical abstract for this article
  • Serial dilution bioassay for the detection of antibacterial potential of
           ZnSe quantum dots and their Fourier transform infra-red spectroscopy
    • Abstract: Publication date: December 2019Source: Measurement, Volume 148Author(s): Ali Reza Khezripour, Dariush Souri, Hadis Tavafi, Mehdi GhabooliAbstractThe aim of this work lies in synthesize of ZnSe nanoparticles (quantum dots: QDs) by microwave (MW) irradiation-assisted method; this method can provide the reduced-dimension particles having high quantum confinements. The Cu-doped and undoped ZnSe QDs were synthesized at the presence of mercaptoacetic acid (MAA) capping agent at different physical-chemical conditions of pH-end (8.0, 10.2, 11.2 and 12.2) of suspension solution, different MW irradiation times (MWIRT = 0, 1, 2, 3, 4 and 6 min) and also at different Cu concentrations (0, 0.1, 0.75, and 1.5 mol%); so, produced QDs were characterized structurally employing Fourier transform infra-red spectroscopy (FTIR) to complete previously published results on their X-ray diffraction (XRD) and UV–Visible spectroscopy. Also, serial dilution bioassay was performed against both gram positive and gram negative bacteria to assess their antibacterial activity; for the antibacterial experiments, four Escherichia coli, Pseudomonas aeruginosa, Staphylococcus aureus, Bacillus cereus bacteria were used as test strains. Results show that these QDs are as potential and promising antibacterial agents, with a dominant (optimal) activity in the cases of (pH = 10.2, MWIRT = 0 min), (pH = 12.2, MWIRT = 0 min; and pH = 11.2, Cu dopant = 1.5%) and (pH = 11.2, MWIRT = 4 min) for Escherichia coli, Staphylococcus aureus, Pseudomonas aeruginosa and Bacillus cereus, respectively. Minimum inhibitory concentration (MIC) results suggest them as novel class of bio-agents. The studied ZnSe QDs had a size of about ∼2 nm and MIC of about 3 ppm for all tested samples. All samples have the same minimum bactericidal concentration (MBC) as MIC, indicating both inhibition and killing of microorganisms. To draw inference about the prominent bio-activity of ZnSe QDs, they should be synthesized in nano-scale, in which effectively enable them to penetrate to the cell walls of both gram-negative and gram-positive bacteria. The FTIR absorption peaks for the synthesized samples, confirm the formation of ZnSe structure, justifying the previously reported results of XRD, field emission scanning electron microscopy (FESEM) and energy dispersive X-ray spectroscopy (EDX); so, the interaction between Se2− and Zn2+ ions were confirmed via FTIR analysis.
  • Rail foot flaw detection based on a laser induced ultrasonic guided wave
    • Abstract: Publication date: December 2019Source: Measurement, Volume 148Author(s): Madhuri Pathak, Sanath Alahakoon, Maksym Spiryagin, Colin ColeAbstractWith the advancements in Railway Engineering in non-destructive testing technologies, a system for the fast detection of rail flaws at earliest stage is in huge demand. Such a system could result in savings in maintenance and would have less operational impact. Most of the research work in this area has been carried out for the defects in rail head and web, while defects in rail foot, which are difficult to access are responsible for derailments and accidents. This research work is focusing on detecting rail foot flaws using non-destructive, non-contact laser induced ultrasonic guided wave-based technique. This paper presents a conceptual technique based on finite element simulations of the propagation of laser induced ultrasonic guided waves to detect cracks in the rail foot. The simulations are performed at different frequencies and varying sensor positions to identify the best suited frequency and sensor location on locomotive for reliable defect detection.
  • Multivariate optimization for maximum capacity of lead acid battery
           through Taguchi method
    • Abstract: Publication date: December 2019Source: Measurement, Volume 148Author(s): Mayank Vyas, Mahaveer Jain, Kapil Pareek, Akhil GargAbstractThe battery is an important electrochemical constituent for sustaining the trouble free and uninterrupted service to its users. Estimation of battery capacity and various states are very important to efficiently allocated available energy and to reduce the possibility of system failure. The estimation could become more complicated when the investigations are to be made under multiple parameters. In this research work, Taguchi method is used to achieve maximum capacity of 12 V 7.2 Ah AMARON SLA SMF battery under condition of C-rate, temperature and relative humidity. A regression model based on the experimental results is developed and validated by high R2 values (97.02%) for maximum capacity attained. Estimated operating conditions obtained for objective function by regression model equation are; C-rate 0.05C, temperature 313 K and relative humidity 25%. The results will shed light on better understanding the effect of multiple parameters on capacity of lead acid battery.
  • A low-cost wireless system of inertial sensors to postural analysis during
           human movement
    • Abstract: Publication date: December 2019Source: Measurement, Volume 148Author(s): Talysson M.O. Santos, Márcio F.S. Barroso, Rodrigo A. Ricco, Erivelton G. Nepomuceno, Érika L.F.C. Alvarenga, Álvaro C.O. Penoni, Ana F. SantosAbstractThe dynamics of the human body has generated considerable recent research interest among scientist devoted to reducing the number of injuries and for performance improvement. In these studies, the investigation is usually addressed by means of commercial devices based on video recordings. However, these systems based on video recordings are usually expensive and require suitable laboratories for their use, which makes it unfeasible to collect data for activities outside controlled environments. In this work, we have shown that it is possible to present similar results with a much lower sampling rate, focusing on the evaluation of minimum and maximum values of the gait. As a result, it has been possible to develop a wearable, compact, portable, low-cost, wireless and embedded system to simultaneously analyze the three-dimensional angular position in eight points. This technology can be used in many sorts of environments. It is also possible to access information in real time with reliable and accurate measurements by means of simple modelling for the use of fusion techniques implemented in the microcontroller. Tests were conducted to evaluate the metrological characteristics of the system using the Complementary Filter (CF) and the Kalman Filter (KF). An algorithm of evolutionary strategies tuned both filters, providing errors of less than 5% for static situations in the measurement of the angular position over the entire system utilization range. Our results have been compared with the commercial system Qualisys Motion-Capture. The statistical method elaborated by Bland and Altman has been used. We have found our method yields a motion analyses in good agreement with results using post-processed video.
  • A novel feature extraction method for roller bearing using sparse
           decomposition based on self-Adaptive complete dictionary
    • Abstract: Publication date: December 2019Source: Measurement, Volume 148Author(s): Junlin Li, Huaqing Wang, Liuyang Song, Lingli CuiAbstractSparse decomposition based on complete dictionary can effectively extract impulse features from weak fault signals. However, compared with the over-complete dictionary, the complete dictionary no longer has redundancy features, and its robustness is reduced, which makes it difficult for sparse signals to extract fault features under weak faults. To overcome this problem, a fault diagnosis method using adaptive complete dictionary via sparse signal is proposed. In particular, in order to improve the adaptability of a complete dictionary, we introduce an adaptive Q-factor wavelet transform (TQWT) algorithm to extract atoms. In the process of extracting atoms, according to the different oscillation characteristics of different Q factors, the adaptive TQWT algorithm is used to extract the atoms which accord with the vibration characteristics of faults. In the process of dictionary constructing, the atom can be extended to a complete dictionary with adaptive characteristics by Toplitz transformation, and then sparse signal with vibration characteristics can be obtained by sparse decomposition. The simulation and experimental results show that the proposed method can extract the frequency domain and time domain characteristics of impulse characteristics more effectively than the sparse signal diagnosis method based on discrete cosine transform (DCT) and discrete Hart transform (DHT) dictionary.
  • Simultaneous measurement of salinity, temperature and pressure in seawater
           using optical fiber SPR sensor
    • Abstract: Publication date: December 2019Source: Measurement, Volume 148Author(s): Yong Zhao, Qi-lu Wu, Ya-nan ZhangAbstractA new fiber optic reflective probe is designed for simultaneous detection of salinity, temperature, and pressure in seawater. As far as we know, it is the first time that these three parameters are measured by an integrated reflex optical fiber sensor. Surface Plasmon Resonance effect inspire by an Au film coated on the fiber’s surface. Photonic crystal fiber (PCF) is chosen as an ideal mode-excitation field. Slow spreading cladding pattern provide a possibility for simultaneous existence of multiple SPR resonance dips. Two kinds of sensitive films (PDMS, SU-8) are coated outside the Au film at different sections. This design makes it possible to form three different sensitive areas, and then three distinct SPR resonance dips appear by optimizing the structure’s parameters. In calibration experiments of an optimized probe, the maximum sensitivity of 0.560 nm/ g/kg, −1.802 nm/°C, and 2.838 nm/MPa are obtained respectively for salinity, temperature, and pressure measurement. Meanwhile, transmission matrix coefficients are determined for cross-sensitive demodulation. This design will have great practical potential if more optimization and process treatments are carried out in the future.
  • Compensation of sound velocity variation based on resampling algorithm for
           natural gas pipeline safety monitoring
    • Abstract: Publication date: December 2019Source: Measurement, Volume 148Author(s): Yang An, Xiaocen Wang, Bin Yue, Zhigang Qu, Liqun Wu, Ronghe ChuAbstractAn active acoustic excitation method based on pulse-compression and envelope subtraction is used for natural gas pipeline safety monitoring. However, when sound velocity changes with ambient temperature, signal-to-noise ratio (SNR) of subtraction result will decrease and severe location error may occur. Therefore, resampling algorithm is utilized to compensate the detection signal drift caused by sound velocity variation. Experiment results demonstrate that the drift of both reflected signal and envelope can be corrected completely after resampling. The SNR of subtraction results are significantly improved to 8.3 dB and 7.34 dB in hydrate plugging and leak detection respectively. The relative location errors of hydrate plugging and leak are respectively reduced from 0.3110% and 0.3494% to 0.0303% and 0.0186%. Besides, the standard deviation of 27 leak location results is 0.0014 m which verifies the repeated location accuracy. The novel method has considerable application prospect in natural gas pipeline safety online monitoring.
  • Measurement of role of transverse and longitudinal members on pullout
           resistance of PET geogrid
    • Abstract: Publication date: December 2019Source: Measurement, Volume 148Author(s): Aali Pant, Manoj Datta, G.V. Ramana, Deepesh BansalAbstractThis paper describes a series of pullout tests that were carried out to investigate the role of transverse and longitudinal members (T & L-members) on pullout resistance of a polyester (PET) geogrid. Pullout tests were conducted on four different geogrid configurations with 0, 4, 8 and 16 T-members at three normal stress embedded in bottom ash and fly ash. The pullout resistance increased with increase in number of T-members and normal stress. However, due to different average particle size, the bearing resistance offered by T-members triggers in fly ash earlier than that in bottom ash. Tests were also conducted to study the influence of spacing and number of L-members. It was observed that the zone of influence of individual L-members overlap at close spacing that reduces the pullout load. This study demonstrates that T-members contribute almost 30–60% towards pullout resistance and exhibit higher contribution at larger confinement stress.
  • Quasi-dispersion of air-coupled ultrasonic signal for angle-dependent
    • Abstract: Publication date: December 2019Source: Measurement, Volume 148Author(s): Zichuan Fan, Yang Zhou, Tianhao Qie, Zhifan WangAbstractIn many practical applications of air-coupled ultrasonic inspection, the accurate direction of the wavefronts of the ultrasound in air is unknown. Thereby, the wave may reach the transducer at an oblique incidence angle. It may lead to misinterpretation of the waveform of the measured wave. This work investigated the quasi-dispersion of planar-wave signal affected by the receiving angle. An analytical model represented as a simplified model implementation was proposed to provide a theoretical prediction of the received signal. A numerical multiphysics model established by COMSOL Multiphysics® was used to demonstrate the signal reception by wavefield visualization. Simulational signals were in excellent agreement with the signals from analytical model. Finally, experiments with the similar configurations of transducers used in analytical and simulational models were conducted. The results confirmed that quasi-dispersion of the air-coupled ultrasonic signal which is highly dependent on incidence angle and wavelength.
  • Omnidirectional field of view structured light calibration method for
           catadioptric vision system
    • Abstract: Publication date: December 2019Source: Measurement, Volume 148Author(s): Xin Chen, Fuqiang Zhou, Ting XueAbstractThere have been improvements to structured light-based catadioptric vision systems (SLCV) to assist with robot navigation and reduce computation time. However, structured-light calibration does not satisfy this assumption. Motivated by this problem, this paper proposes a new approach for estimating the position of the structured lights of an SLCV system. Structured light points projected by lasers are reflected into the image plane through a conic mirror in order to view an omnidirectional image containing multiple structured light points. Efficient calibration of the laser location is possible based on the 2D information of the laser points, subject to the camera parameters and the mirror position. The performance of this method is evaluated experimentally using simulated and real data, and demonstrates that the proposed method is more robust and provides a higher measurement accuracy with a lower number of images, thus verifying the method’s feasibility.
  • Electrochemical detection of bisphenol B based on poly(Prussian
           blue)/carboxylated multiwalled carbon nanotubes composite modified
    • Abstract: Publication date: December 2019Source: Measurement, Volume 148Author(s): Yi Xing, Guanlan Wu, Ying Ma, Yangyang Yu, Xing Yuan, Xiaolin ZhuAbstractA simple and highly sensitive electrochemical sensor for the determination of bisphenol B (BPB) based on a glassy carbon electrode (GCE) modified with Prussian blue (PB) and carboxylated multi-walled carbon nanotubes (MWNTs-COOH) was constructed. The PB/MWCNTs-COOH/GCE was characterized by emission scanning electron microscopy, X-ray diffraction, electrochemical impedance spectroscopy, and cyclic voltammetry. Due to the synergistic effect, the PB/MWCNTs-COOH/GCE remarkably enhanced the oxidation of BPB, which improved the anodic peak current of BPB significantly. Under the optimum conditions, the linear response range of BPB was between 5 × 10−8 and 1.75 × 10−4 M with the detection limit (S/N = 3) of 5 × 10−10 M. Additionally, the PB/MWCNTs-COOH/GCE revealed excellent stability, repeatability and reproducibility. Moreover, it was successfully applied in the determination of BPB in real samples. This study provided a sensitive and simple sensor for the quantitative detection of BPB in the environment.
  • A new leaky piston identification method in an axial piston pump based on
           the extended Kalman filter
    • Abstract: Publication date: December 2019Source: Measurement, Volume 148Author(s): D. Bensaad, A. Soualhi, F. GuilletAbstractVolumetric losses are essential to ensure proper lubrication of moving components in an axial piston pump (APP). However, amplification of these volumetric losses can be observed when one or more pistons of the APP degrade due to friction and contaminated fluid. This amplification of volumetric losses due to a worn piston is often called a piston leak. The latter disturbs the output pressure signal and considerably reduces the efficiency of the pump. It also generates significant vibrations that can lead to the resonance of the pump structure. In this context, it is necessary to implement a diagnosis tool to identify the worn piston among the others. This will allow effective maintenance interventions by changing only the worn piston instead of all pistons.This paper presents a new approach based on the physical model of the pump to identify the worn piston from the healthy ones. It begins by modelling the dynamic comportment of the pump in a nonlinear state model. Then, the extended Kalman filter (EKF) is adapted to estimate pressure in piston chambers. This estimation gives the possibility to observe the pressure into each piston chamber and then allows the identification of the worn piston. The proposed approach is validated on an APP test rig. The obtained results prove the efficiency of the proposed approach in identifying the worn piston.
  • Error correction of temperature measurement data obtained from an embedded
           bifilar optical fiber network in concrete dams
    • Abstract: Publication date: December 2019Source: Measurement, Volume 148Author(s): Zhipeng Liang, Chunju Zhao, Huawei Zhou, Quan Liu, Yihong ZhouAbstractConventional distributed optical fiber systems employed for internal temperature sensing in concrete dams suffer from low survival rate, insufficient measurement data, and low-accuracy temperature measurements that are subject to large fluctuations. Therefore, the present study proposes a bifilar optical fiber embedding technique running within each of the concrete dam blocks forming a dam. The proposed fiber optic network design is based on multiple considerations, including the embedding requirements of optical fiber to ensure good system longevity, the requirements of internal temperature monitoring in concrete dams to ensure the capture of adequate monitoring data, and the temperature measurement principle of distributed temperature sensing (DTS) systems to develop effective error correction methods. In terms of error correction, the light intensity attenuation caused by transmission- and wavelength-related losses is calculated based on the symmetrical temperature measurement points of the primary and secondary strands of the embedded bifilar optical fiber in conjunction with error correction theory to correct for temperature measurement fluctuations and thereby ensure the capture of accurate and stable temperature measurement data. Experimental error correction test results demonstrate that the mean absolute error (MAE) and root mean squared error (RMSE) of the error corrected temperature data obtained under various temperature conditions are reduced by 0.28 °C and 0.34 °C, with fluctuations that are decreased by 53.4% and 52.4%, respectively. The results derived from an actual engineering application under construction demonstrate that the survival rate of the embedded bifilar optical fibers is 100%. In addition, the average MAE and RMSE values of the temperature data obtained by the DTS system during the first water cooling stage are reduced by 0.14 °C and 0.22 °C, and their fluctuations are decreased by 41.5% and 47.0%, respectively. These results verify the reliability and feasibility of the error correction method proposed in this paper, and the method is demonstrated to provide reliable technical support for obtaining stable and high-precision DTS temperature data in concrete dams.
  • Deformation measurement of high-speed rotating drone blades based on
           digital image correlation combined with ring projection transform and
           orientation codes
    • Abstract: Publication date: December 2019Source: Measurement, Volume 148Author(s): Lianpo Wang, Songlin Bi, Xiang Lu, Yonggang Gu, Chao ZhaiAbstractDigital image correlation (DIC) is a versatile non-contact optical measurement method, but it still has many shortcomings in theory and application. For example, the traditional DIC method has difficulty obtaining the desired result when the surface of the test object is rotated substantially or the deformation involves large rotation. Some scholars argue that a rotation angle greater than 7° will not work with the DIC algorithm, and this phenomenon is called decorrelation. To solve this problem, this study proposes the rotation-invariant DIC (RI-DIC) method that combines rotation-invariant template matching with traditional DIC. A pre-matching method based on ring projection transform (RPT) and orientation codes (OC) is proposed to provide the initial values for the DIC iteration process. The algorithm consists of three stages. In the first stage, the RPT process is used to convert the 2D template in a circular region into a 1D grey-level signal as a function of radius, and the template matching based on RPT is used to obtain a series of candidate points. The advantages of RPT process are the characterisation of its rotation invariance and the reduction of computational complexity. In the second stage, a fine matching process based on OC is performed on a limited number of candidate points to obtain the integer pixel matching position and the initial value. Finally, the inverse compositional Gauss–Newton (IC-GN) iteration method is used to further calculate the displacement and strain information accurately on the basis of the initial values. The novelty of this paper is to fuse the ring projection transform and orientation codes in machine vision into the traditional DIC algorithm, finally propose the RI-DIC algorithm. By the proposed method, we can measure the strain generated by the centrifugal force of a drone blade rotating at a high speed. Experimental results indicate that the method can accurately measure the surface deformation of a test object at any rotation angle.
  • Reliability of the estimation of uniform corrosion rate of Q235B steel
           under simulated marine atmospheric conditions by electrochemical noise
           (EN) analyses
    • Abstract: Publication date: December 2019Source: Measurement, Volume 148Author(s): Da-Hai Xia, Chao Ma, Yashar Behnamian, Sansan Ao, Shizhe Song, Likun XuAbstractThis paper aims to monitoring the atmospheric corrosion of Q235B steel by electrochemical noise (EN) technique, and both statistical parameters and frequency domain analysis are used to quantify the corrosion rate. The reliability of EN measurement was evaluated by electrochemical impedance spectroscopy (EIS). Experimental results indicate that electrolyte resistance have an impact on EN measurement but it can be discarded if it is much lower than the impedance of working electrode (WE). Theoretical predictions using Thevenin equivalent circuit model reveal that spectral noise impedance is not equal to impedance module as estimated by EIS, and a relationship between them is derived. Power spectral density (PSD) obtained from experimental data further verified the theoretical predictions.
  • Calibration method of light-field camera for photogrammetry application
    • Abstract: Publication date: December 2019Source: Measurement, Volume 148Author(s): Yue Ji, Jun WuAbstractAs a novel imaging method, the light-field camera can extract different ray traces in the space due to the micro-lens array fixed ahead of the imaging sensor. However, when it is used in photogrammetry such as light pen orientation, attitude estimation and indoor navigation, the classical collinear constraint cannot be applied directly since the refraction effect from the main lens. Therefore, this paper has proposed a mathematical model to calibrate the positions of sub-apertures on the main lens by using bundle adjustment algorithm. Firstly, the reference position for the sub-apertures will be calibrated by using center sub-aperture images. Secondly, the virtual imaging points of the target bar through different sub-apertures can be obtained by the focal length of the main lens. Then the sub-apertures on the main lens can be calculated by using bundle adjustment algorithm. Finally, the experiments results verified the accuracy and effectiveness of the proposed method.
  • Design and experimental study of zero-compensation steering gear load
           simulator with double torsion springs
    • Abstract: Publication date: December 2019Source: Measurement, Volume 148Author(s): Bo Zhang, Cheng Li, Tao Wang, Zhuo Wang, Hongwen MaAbstractAs one of the main actuators of the missile guidance control system, the steering gear is used to change the missile flight direction. In order to improve the accuracy of the load simulator used to test missile steering gears, a mechanical servo load simulator design, based on torsion springs, is presented. In the design process, in order to avoid the zero hysteresis portion of the torsion spring characteristic curve, the innovative method of zero-compensation using the reverse arrangement of the double torsion spring is proposed. Finally, by using the process servo calibration test and the actual test of the steering gear, the zero error is effectively reduced while the load gradient is satisfied, and the accuracy of the load platform is improved. The results obtained strongly indicate the feasibility of the proposed method. The zero error of the double torsion spring structure is less than the required 1%.
  • Physicochemical properties of Iranian ziziphus honey and emerging approach
           for predicting them using electronic nose
    • Abstract: Publication date: December 2019Source: Measurement, Volume 148Author(s): Saeed Faal, Mohammad Loghavi, Saadat KamgarThe aim of this paper is development and evaluation of an electronic nose as a non-destructive system for predicting the physicochemical parameters of honey including ash content (AC), free acidity (FA), moisture content (MC) and pH based on its aroma. To verify the authenticity of the honey samples the HPLC analysis carried out. Artificial neural network (ANN) and Support Vector Machine (SVM) models were applied to the features extracted from the sensors responses to predict AC, FA, MC and pH. The developed models for prediction of the physicochemical parameters showed high performance based on the honey headspace gases and the best results for predicting the AC, FA, MC and pH obtained from the ANN model which the R2 values were 0.838, 0.918, 0.926 and 0.933, respectively. The results proved feasibility and applicability of using the developed e-nose as a non-destructive system for predicting the physicochemical properties of honey.Graphical abstractGraphical abstract for this article
  • Adaptive compensation for measurement error in remote sensing of mobile
           source emissions
    • Abstract: Publication date: December 2019Source: Measurement, Volume 148Author(s): Xugang Xi, Ziyang Sun, Tong Hua, Peng Jiang, Seyed M. Miran, Xiaolu LiUsing remote sensing technology to monitor mobile pollution sources is an advanced technology to prevent air pollution. This paper proposes an error compensation model that can prevent remote sensing from being subjected to complex and variable environmental disturbances. Using this novel method, the measurement error prediction model under multiple interferences is established by Extreme Learning Machine. Then, the actual measurement process is transformed into the multi-sensor virtual observation model that is used to achieve the sequence decomposition of the original sequence. Finally, the fusion of virtual observation sequences is performed by the Adaptive Kalman Filter. Transfer Entropy is used to represent the multi-disturbance unbalance measurement and optimize the observation noise covariance coefficient in Adaptive Kalman Filter. Experimental results showed that compared with traditional method, our model performed better. The results indicated that our method can quickly and effectively compensate the measurement error and improve the environmental adaptability of the instrument.Graphical abstractGraphical abstract for this article
  • Soft sensors design in a petrochemical process using an Evolutionary
    • Abstract: Publication date: December 2019Source: Measurement, Volume 148Author(s): Gustavo A.P. de Morais, Bruno H.G. Barbosa, Danton D. Ferreira, Leonardo S. PaivaAbstractThe downhole pressure is an important variable used to optimize the oil production in deep-water oil wells. However, due to its localization at the seabed, its sensor breaks down easily. Thus, a parameter-less Evolutionary Algorithm, called Evolutionary Algorithm with Numerical Differentiation (EAND), is proposed in this work for designing soft sensors to predict the downhole pressure. Results show that the EAND performs good balance between local and global searches, providing the best results in 17 out of the 20 optimization problems, and achieving the fastest convergence in 16 simulated problems. The proposed algorithm yielded the best soft sensors under the five offshore oil wells studied when compared to other identification methods. Three kinds of nonlinear models for prediction were implemented, and ensembles composed of decision trees (Random Forest) obtained the best results. The Mean Absolute Percentage Errors (MAPE) found when predicting the downhole pressure by the identified soft sensors ranged from 0.1453% to 0.788%, which are very satisfactory.
  • A hybridized methodology of different wavelet transformations targeting
           medical images in IoT infrastructure
    • Abstract: Publication date: December 2019Source: Measurement, Volume 148Author(s): Tamara K. Al-Shayea, Constandinos X. Mavromoustakis, Jordi Mongay Batalla, George MastorakisAbstractThe Internet of Things (IoT) paradigm has become a vital part of all significant scientific sectors, including the healthcare domain. Medical images in the healthcare sector are indispensable items that are usually susceptible to distortion once they are shared and transferred via the Internet. The sector faces the distinct and constant challenge of preserving medical data, which can be manipulated by various malicious attacks, in turn potentially compromising the patients’ diagnostic data. In this situation, such medical data ought to be private, with access only granted to patients and physicians. This paper elaborates on a hybrid measurement technique for digital image watermarking that utilizes medical images (X-ray, MRA, and CT), which are an extremely robust method for protecting clinical information. The authors explore various different wavelet families, in addition to hybridization between these wavelets. These are carried out on three levels decomposition of Discrete wavelet transformation (biorthogonal 6.8 wavelets, biorthogonal 3.5 wavelets, biorthogonal 5.5 wavelets, reverse biorthogonal 6.8, reverse biorthogonal 3.5, reverse biorthogonal 5.5, discrete meyer, symlets 5, symlets 8 coiflets 4 wavelet, and coiflets 5 wavelet transform). Each level uses various types of wavelet transformation to present the watermarked image, and then extracts the medical watermark from the original watermarked image. The results of diverse types of attack have been compared, while the proposed measurement technique's performance is evaluated using statistical parameters (MSE, PSNR, SSIM, and NC). This in turn measures the quality of the image, which so far shows promising results.
  • A CFD simulation of the liquid-cooled pipe conductors for the high power
           and high frequency power electronic circuits
    • Abstract: Publication date: December 2019Source: Measurement, Volume 147Author(s): Selami BalciAbstractIn recent years, depending on the developments in semiconductor technology; the performance of power electronic circuits has been increased significantly with higher power and higher switching frequency capability. However, the higher switching frequency increases both core and winding losses of the magnetic components (such as inductor and transformer) contained in the power electronics circuits. In high frequency inductors, during the rippled current flow, the winding conductors cause abnormal temperature rises due to the skin and proximity effects. This phenomenon cannot be precisely determined by mathematical methods in the design phase. In this study, the liquid cooled pipe conductors are recommended in the windings of high-frequency and high-power inductors employed in the power electronic circuits, which can be used in renewable energy systems and electric vehicles. These pipe conductors have been modeled with the Ansys-Mechanical Fluent software and the temperature values have been determined with the computational fluid dynamics (CFD) analysis. Thus, the cooling performance for the inductor winding versus the liquid circulation through the copper pipe conductor has been reported.
  • Adaptive signal fusion based on relative fluctuations of variable signals
    • Abstract: Publication date: December 2019Source: Measurement, Volume 148Author(s): Zong Meng, Zuozhou Pan, Zijun Chen, Ying ShiAbstractTo solve the problem of the total mean square error of the traditional random weighting algorithm being much larger when the target signal is variable than when the signal is constant, an improved adaptive random weighting algorithm is proposed. To bring the estimated value closer to the true value, the algorithm adjusts the proportional relationship between the current acquisition signal and the historical acquisition signal adaptively by using the relative fluctuation value of the collected signal. Because the relative fluctuation value can be adjusted autonomously according to the signal variation, it can be combined with the traditional random weighting algorithm very successfully. Numerical simulations demonstrate the effectiveness of the proposed fusion method.
  • Effect of perlite powder and silica fume on the compressive strength and
           microstructural characterization of self-compacting concrete with
           lime-cement binder
    • Abstract: Publication date: December 2019Source: Measurement, Volume 147Author(s): J. Esfandiari, P. LoghmaniAbstractThis study evaluated the short and long term mechanical properties of self-compacting concrete (SCC) with a lime-cement binder, silica fume (SF), perlite powder (PP), and silica fume-perlite powder mixture (SF-PP) as additives. The aim of the present study was to investigate the effects of different amounts of additives on the fresh and mechanical properties of SCC. Also in this research cement-lime binder was replaced by SF, PP, and SF-PP at 0%, 5%, 10% 15%, and 20%, respectively. The optimum percentage was 17% for SF, 6% for PP and 6% for SF-PP on 28th and 90th days to obtain maximum compressive strength. The results showed that water absorption, dry density, of the 28-days compressive strength increased with an increase in silica fume (SF) content. The contents of PP and SF-PP replacement also influenced the resulting SCC, but the latter had a better effect on the concrete. The highest compressive strength of SCC was observed at 17%, 6%, and 6% for SF, PP and SF-PP, respectively (on days 90). When 10% lime powder was added instead of cement, the optimum usage of SF dropped to below 20%. The optimum usage of SF for normal concrete is above 20%.
  • Quantitative estimation of soda ash as an adulterant in aqueous sucrose
           solution by employing electrical impedance and capacitance spectroscopy
    • Abstract: Publication date: December 2019Source: Measurement, Volume 148Author(s): Chirantan Das, Subhadip Chakraborty, Nirmal Kumar Bera, Dipankar Chattopadhyay, Anupam Karmakar, Sanatan ChattopadhyayThis study analyses measured values of impedance, capacitance and conductance for pure sucrose-DI water solution and when adulterated with different wt% of soda ash (Na2CO3). For pure sucrose-DI water solution, these electrical parameters vary in a quasi-oscillatory nature with increasing sucrose concentration; however, it varies linearly for adulterant wt% ≥ 1%. For pure sucrose-DI water solution, impedance values, in our test setup, are observed to be ranging from 141.53 kΩ to 230 kΩ whereas capacitance and conductance values range from 40.53 pF to 43.91 pF and 4.14 µS to 6.73 µS, respectively, for different sucrose volume fractions. However, under adulterated conditions (upto 5%) such values change from 157.15 kΩ to 107 Ω for impedance, 42.5 pF to 72 µF for capacitance and 6.06 µS to 8.9 mS for conductance, respectively. Coefficient of sensitivity has been extracted which indicates that the system can detect a minimum of 1% Na2CO3 in aqueous sucrose solution.Graphical abstractGraphical abstract for this article
  • A novel robust depth estimation method based on optimal region selection
    • Abstract: Publication date: December 2019Source: Measurement, Volume 148Author(s): Man Chen, Yong Zhong, Zhendong Li, Xiang Zhao, Jin WuAbstractIn this paper, a novel robust depth estimation method based on optimal region selection is proposed with improved anti-noise capability and structural retention. In particular, this new scheme provides the practitioners with a better de-noising ability by means of improving the non-subsampled contourlet transform (NSCT) features. Moreover, an optimal region selection technique is developed to further suppress the noise in focus measure. In order to make the features more prominent, the derivatives of features along optical axis are normalized for weighting in optimal region selection process. Experimental results demonstrate that the proposed method has superiority on better anti-noise ability, higher structural retention performance, compared with the existing representative methods.
  • Visualization of shockwave behavior in water and gelatin
    • Abstract: Publication date: December 2019Source: Measurement, Volume 148Author(s): Daisuke Inao, Shigeru Tanaka, Tomoya Yamashita, Kazuyuki HokamotoAbstractExplosive welding is a popular method that is utilized to bond different types of metals. In particular, with the use of underwater explosive welding technique, the uniform acceleration of a thin plate over a very short flying distance is possible, which makes the technique suitable for the welding of thin plates onto a base plate to modify various properties of the surface of interest for protection against extreme environments. However, the use of water complicates the setup of the assembly, and therefore, in this study, we attempt to use other pressure-transmitting media, such as gelatin, which exhibits shockwave propagation similar to water. The similarity of shockwave propagation of the two materials is confirmed via optical observations utilizing a high-speed camera for two types of explosives. Thus, our findings confirm the viability of the use of gelatin as a pressure-transmitting medium for explosive welding.
  • An algorithm for measuring the hydraulic jump height of an airfoil in a
           water table
    • Abstract: Publication date: December 2019Source: Measurement, Volume 148Author(s): Ian C. Garretson, François M. Torner, Jörg Seewig, Barbara S. LinkeAbstractIncorporating visualization in to research and education of fluid flows necessitates the use of either a wind tunnel or a water table. Water tables can be utilized for performing analogous dispersion wave experiments, in which wave height is a critical measurement. This paper describes an initial, automated water height measurement technique using photo analysis and prismatic light bending. Three algorithms for analyzing overhead images of the water jump are described. The algorithms include the fringe line detection and prism analogy, and a Discrete Fourier Transform and Convolution Method.
  • Application of transmissibility measurements to operational modal analysis
           of railway, highway, and pedestrian cable-stayed bridges
    • Abstract: Publication date: December 2019Source: Measurement, Volume 148Author(s): Qian Sun, Wang-Ji Yan, Wei-Xin Ren, Ling-Ling LiuAbstractTwo transmissibility-based operational modal analysis (TOMA) schemes, i.e., the classic TOMA method utilizing measurements under multiple loading conditions, and the power spectral density transmissibility (PSDT) method resorting to multiple reference outputs under one loading condition, are further investigated in this study. For the classic TOMA approach, the issue of requiring multiple loading conditions is properly addressed in ambient vibration testing. Based on the unique properties of transmissibility, the frequencies can be extracted by varying either loading conditions or reference outputs, while the mode shapes can be estimated by a singular value decomposition of the transmissibility matrix. The applicability of TOMA approaches is evaluated through three typical large-scale cable-stayed bridges, including a railway bridge, a highway bridge, and a pedestrian bridge. A comparative study of these large cable-stayed bridges is carried out to gain more insights into the dynamic properties of large-scale cable-stayed bridges.
  • Pixel-based operating modes from surveillance videos for structural
           vibration monitoring: A preliminary experimental study
    • Abstract: Publication date: December 2019Source: Measurement, Volume 148Author(s): A. Zare Hosseinzadeh, P.S. HarveyAbstractThis paper presents a practical and cost effective method for vibration monitoring using multiple surveillance cameras distributed throughout (within) a building structure. Robust feature points in surveillance footage are identified and tracked frame-by-frame (with the Kanade-Lucas-Tomasi tracker) to extract the pixel motions. The relative pixel motions from multiple locations within the structure are analyzed in the frequency domain to estimate dynamic characteristics of the monitored structure (e.g., the dominant frequencies), as well as the pixel-based operating modes. These pixel-based modes importantly are in pixel units, eliminating the need to converted to engineering (physical) units. The method is verified through an experimental parametric study on a three-story lab-scale building structure (with three surveillance cameras) excited by broadband white noise signals. The accuracy and repeatability of the method are assessed to evaluate its application for structural health monitoring.
  • A framework for high-resolution frequency response measurement and
           parameter estimation in microscale impedance applications
    • Abstract: Publication date: December 2019Source: Measurement, Volume 148Author(s): Roberto G. Ramírez-Chavarría, Matias I. Müller, Robert Mattila, Gustavo Quintana-Carapia, Celia Sánchez-PérezAbstractElectrical impedance spectroscopy (EIS) is a tool for characterizing the electrical behavior of matter. Nevertheless, most of the work is focused on purely experimental results, leading aside alternative measurement and estimation techniques. In this paper, we introduce a framework for spectral measurements and parameter estimation applied to EIS. There are two methods in the proposal running independently: frequency response function based non-parametric estimation, and parametric recursive estimation. The former provides consistent estimates even in the presence of noise and works with batches of data. Whilst the latter gives consistent parametric estimates under the right model structure. The proposed platform is designed around a reconfigurable device, which comprises minimal hardware design and digital signal processing. We test the system with a multisine signal by measuring calibration circuits and colloidal samples at microscale. Results show that this method outperforms the state-of-the-art techniques for impedance measurement applications, exhibiting low uncertainty and physical interpretation.
  • A new wind turbine health condition monitoring method based on VMD-MPE and
           feature-based transfer learning
    • Abstract: Publication date: December 2019Source: Measurement, Volume 148Author(s): He Ren, Wenyi Liu, Mengchen Shan, Xin WangAimed at the problem that the signal data of wind turbine faulty gearbox is difficult to obtain and the health condition is difficult to diagnose under variable working conditions, a fault diagnosis method based on variational mode decomposition (VMD) multi-scale permutation entropy (MPE) and feature-based transfer learning (FTL) is proposed. According to the vibration signal characteristics of wind turbines, a series of mode components are obtained by transforming the signals under variable conditions. The MPE of the mode components is combined with the signal time domain features as a feature vector to be input into the transfer learning algorithm. The source domain and the target domain data belong to different working conditions, so the traditional machine learning methods are not ideal for fault classification. The method adopted in this paper minimizes the covariance between the source domain and the target domain through a linear transformation matrix, and reduces the difference of data distribution between the source domain and the target domain. Then, the feature vectors of the covariance-aligned source domain and the target domain are input into the support vector machine (SVM) for training and testing. Experiment shows that the proposed covariance alignment (COVAL) of fault features has higher accuracy in rolling bearing multi-state classification under variable working conditions compared with other methods.Graphical abstractGraphical abstract for this article
  • A new fast morphological geodesic active contour method for lung CT image
    • Abstract: Publication date: December 2019Source: Measurement, Volume 148Author(s): Aldísio G. Medeiros, Matheus T. Guimarães, Solon A. Peixoto, Lucas de O. Santos, Antônio C. da Silva Barros, Elizângela de S. Rebouças, Victor Hugo C. de Albuquerque, Pedro P. Rebouças FilhoAbstractThis work proposes a new adaptive approach to lung segmentation based on a non-parametric adaptive active contour method (ACM) without previous training using the new Fuzzy Border Detector, called Fast Morphological Geodesic Active Contour (FGAC). Performance was evaluated with 72 lung images of volunteers that were with fibrosis, chronic obstructive pulmonary disease or were healthy. A manual segmentation by a medical specialist was considered the gold standard. The mean time of segmentation of seventy-two the two lungs was 1.98 s. This was the best average time among all the other segmentation methods compared here: GVF (240 s), VFC(30 s), OPS Euclidean (5.86 s), SISDEP (4.90 s), and CRAD (2 s); thus showing its potential for real-time applications. The FGAC showed good results in all similarity metrics compared in this work like the Jaccard Index (92.73%), Dice coefficient (96.19%) and Matthew correlation coefficient (95.54%), and also achieved good results in sensitivity (99.21%), and accuracy (98.86%). The new approach showed quantitative indexes better than the traditional methods VFC, GVF, RHT mod, RHT multi. Moreover, we evaluated the proposed method against the supervised techniques OPS-Euclidean, SISDEP, CRISP and CRAD. Our approach achieved superior or equivalent results to these methods, however with a shorter convergence time. These results had good indexes suggesting that the proposed approach can be used to aid medical diagnosis in pulmonology.
  • Experimental research on a novel optic fiber sensor based on OTDR for
           landslide monitoring
    • Abstract: Publication date: December 2019Source: Measurement, Volume 148Author(s): Yong Zheng, Zheng-Wei Zhu, Wan-Jie Li, Dong-Ming Gu, Wang XiaoAbstractIn this paper a novel optic fiber sensor (OFS) based on optical time domain reflectometer (OTDR) with simple construction and innovative structure was developed for landslide monitoring. The instrument had a maximum measurement distance and an effective initial measurement displacement and a low economic cost of 36 mm, 0.98 mm and $ 0.45/m. A direct-shear experiment with an OFS was conducted to investigate its effectiveness in monitoring the damage from shear sliding on rock slopes. A detailed field-monitoring test of the proposed OFS on a shallow artificial slope was conducted and the progressive deformation behavior of the slope was accurately captured by the OFS. In addition, it is possible to connect these OFSs in series to explore the underground properties of deep-seated landslides. This capability supports the promising application of the OFS in civil engineering for real-time monitoring of the stability of slopes, foundation pits and dams.
  • Vibration signal denoising using partial differential equations of
           arbitrary order
    • Abstract: Publication date: December 2019Source: Measurement, Volume 148Author(s): Hongji Ren, Aijun Yin, Quan ZhangAbstractIn this paper, partial differential equations (PDE) denoising characteristics are investigated and a unified vibration denoising model is proposed based on arbitrary order PDE. The numerical solution for PDE filters with arbitrary order is demonstrated. The noise reduction features of the proposed model are analysed on Gaussian white noise, Pearson noise and Weibull noise. The realization of the PDE filter generally include the following steps: (1) Obtain the discretization equation according to the given order using the backward Euler scheme; (2) Compute the grid ratio according to the given order, the cut-off frequency and the sample frequency; (3) acquire the filter matrix. Numerical simulations are conducted and the results indicate that the proposed method exceeds relevant works in noise reduction and time-consuming performances. A shaft centreline orbit experiment has also been conducted to verify the efficacy of the proposed method in field application.
  • Development and performance evaluation of an electromagnetic tracking
           system for surgery navigation
    • Abstract: Publication date: December 2019Source: Measurement, Volume 148Author(s): Gregorio Andria, Filippo Attivissimo, Attilio Di Nisio, Anna Maria Lucia Lanzolla, Pietro Larizza, Sergio SelicatoAbstractIn Image Guided Surgery (IGS), an electromagnetic tracking system is used nowadays to locate surgical instruments in the patient's anatomical 3D model. In this work we illustrate the development and the evaluation of a new Electromagnetic Tracking system (EMTS) able to provide a large tracking volume.The innovation of this proposed EMTS consists in the development of the Field Generator (FG), which includes five properly designed coils. Attention has been paid to the magnetic field generated by each coil in order to comply with the safety limits imposed by IEEE Stds C95.1 and C95.6. The simultaneous transmission of the five coils is possible thanks to a suitable frequency division multiplexing.To validate the proposed design, a detailed noise analysis was performed with several experimental tests in different working conditions with the aim of evaluating measurement errors.Actual performance of the system in reconstructing sensor position has been quantified by using a suitable interpolation technique. In particular, mean position error and standard deviation were evaluated for different distances of magnetic sensor from field generator.
  • Enhancement of activated tungsten inert gas (A-TIG) welding using
           multi-component TiO2-SiO2-Al2O3 hybrid flux
    • Abstract: Publication date: December 2019Source: Measurement, Volume 148Author(s): Atul Babbar, Akhilesh Kumar, Vivek Jain, Dheeraj GuptaA novel technique of using activated flux in Tungsten inert gas (TIG) welding is used in the present investigations. The effect of hybrid multi-component surfactant (flux) is discussed in terms of depth of penetration (DOP), micro-hardness, tensile strength, and metallurgical traits. The activated TIG welding has been carried for different thickness of workpiece material with three factors current, travel speed, and flow rate at three levels. The results revealed a significant increase in the depth of penetration on using activated flux. The maximum DOP achieved is 8.283 mm with current 110 A, speed 82 mm/min and flow rate of 14 L/min. The results obtained from tensile test demonstrates that A-TIG welding produces welds with better strength. Radiography highlight defect-free welds on using activated flux. The outcomes of the present study confirm the applicability of this low-cost welding technique for joining SS-304 stainless steel thick sheets for the improved endowment.Graphical abstractGraphical abstract for this article
  • A deep capsule neural network with stochastic delta rule for bearing fault
           diagnosis on raw vibration signals
    • Abstract: Publication date: December 2019Source: Measurement, Volume 148Author(s): Tianyou Chen, Zhihua Wang, Xiang Yang, Kun JiangAbstractIn recent years, deep learning techniques are explored unceasingly for machinery fault diagnosis. The vibration signal of faulty rotating machines contains distinct periodic impacts, and hence is the ideal candidate for the model input. However, there are still three challenges in deep learning on raw vibration signals: (1) The shifts of the fault impacts among the input samples prone to cause misdiagnosis; (2) The working load is always changing; (3) The background noise such as the vibration from non-goal machines is inevitable. Therefore, a novel method called deep capsule network with stochastic delta rule (DCN-SDR) is proposed for rolling bearing fault diagnosis. DCN-SDR takes raw temporal signal as input and achieves very high accuracy under different working loads. Moreover, the model performs outstandingly under noisy environment via a regularization method based on SDR. The network visualization is demonstrated and analyzed. Comparing with the state-of-the-art methods, superiority of the proposed method is verified.
  • Asphalt road surface vibration and force distribution generated by pickup
           truck braking
    • Abstract: Publication date: December 2019Source: Measurement, Volume 148Author(s): Preecha Yupapin, Nithiroth PornsuwancharoenAbstractThis paper presents a method for dynamic vibration and force measurement using a microcontroller. In the experiment, data were obtained by vibration frequency measurement at the asphalt road surface when the vehicle brakes were applied, and the data were analyzed using additional equipment and software. By using the SW-420 device, frequencies in the range of 10–1000 Hz were applied and tested. The results obtained indicated that the proposed system can be used to determine the force acting on the road surface while the vehicle is in motion. The estimated forces were within the range of 0.20–4.10 × 1010 N at velocities of 20–100 km·h−1. A relative maximum error of 0.20% was achieved.
  • Research on the on-line dimensional accuracy measurement method of conical
           spun workpieces based on machine vision technology
    • Abstract: Publication date: December 2019Source: Measurement, Volume 148Author(s): Gangfeng Xiao, Yongting Li, Qinxiang Xia, Xiuquan Cheng, Weiping ChenAbstractAn on-line dimensional accuracy measurement method was proposed based on machine vision technology to realize the real-time measurement of straightness and roundness of spun workpieces during spinning. An image acquisition system was developed to obtain the real-time images of conical spun workpiece and the camera calibration was conducted. The edges of the conical spun workpiece were extracted by region of interest (ROI) extraction, image deblurring, denoising and edge detection. The straightness and roundness of the spun workpieces were automatically calculated by writing the calculation program. The reliability of on-line dimensional accuracy measurement system was verified by comparing with measurement results of 3D measuring machine. The results show that the straightness and roundness calculated by measurement system confirm well with that measured by 3D measuring machine, the relative errors between which are less than 10%, and the average detection time of straightness and roundness is 98.5 ms and 69.3 ms, respectively.
  • Bearing fault diagnosis through stochastic resonance by full-wave signal
           construction with half-cycle delay
    • Abstract: Publication date: December 2019Source: Measurement, Volume 148Author(s): Kuo Chi, Jianshe Kang, Rusmir Bajric, Xinghui ZhangAbstractStochastic resonance (SR) can enhance the weak fault-induced impulses in envelope signal. However, envelope signal is a unipolar half-wave signal which is worse than bipolar full-wave signal for SR effect. To convert envelope signal into bipolar full-wave signal, two full-wave signal construction (FSC) methods based on mirror-cycle-add (MCA) operation are proposed called FSCBME and FSCBHCD. FSCBME is to find the lag time, an important MCA parameter, that maximizes the energy of the constructed full-wave signal. FSCBHCD is to make the lag time equal to half of the driving signal cycle. Regarding the constructed full-wave signal as SR input, two novel SR methods are proposed called FSCBMESR and FSCBHCDSR. Simulations and cast study are done. Simulations prove that the robustness and anti-noise capability of FSCBHCD is better than FSCBME, and FSCBHCDSR performance is better than FSCBMESR performance. Case study proves that FSCBHCDSR is more effective than FSCBMESR in bearing fault diagnosis.
  • Wheel dynamometer system for aircraft landing gear testing
    • Abstract: Publication date: December 2019Source: Measurement, Volume 148Author(s): Jarosław Pytka, Jerzy Józwik, Piotr Budzyński, Tomasz Łyszczyk, Arkadiusz Tofil, Ernest Gnapowski, Jan LaskowskiAbstractThe aim of this study was to design, develop and apply practically a wheel dynamometer for aircraft landing gear testing. The dynamometer system was designed to measure two force components acting along the longitudinal and vertical axes of the wheel as well as and three moments acting around the longitudinal, transversal and vertical axes. It consists of a sensor unit that is embedded in the wheel hub, a modified rim with a tyre as well as a data acquisition and transfer system that enables the measured signals to transfer wirelessly to a portable computer or another device (smartphone, tablet). The sensor unit was developed based on strain gage measurement technology. The prototype system was calibrated in a stationary test stand, then installed on a PZL 104 Wilga 35A for airfield tests. Primary test measurements were performed with the aircraft taxiing at “walking man” speed and proved system’s performance. Certification for ground and flight tests of airplanes has been considered for the presented dynamometer system.
  • Gap-tolerance control for friction stir butt welding of 2A14 aluminium
    • Abstract: Publication date: December 2019Source: Measurement, Volume 148Author(s): He Ma, Yue Wang, Zhijie Tian, Linyu Xiong, Yanhua ZhangAbstractHerein, we report the effects of gap variation upon the joint quality and thermomechanical behaviour of 2A14-T6 aluminium alloy friction stir butt welding. Based on the optimal weld pitch, gap-free and variable gap (from 0 to 2 mm in the weld) friction stir welding (FSW) experiments were conducted. The results indicate that welds without metallurgical defects were obtained up to a butt gap of 0.8 mm; however, voids and tunnel defect occurred at gap widths of 1.6 and 2 mm, respectively; moreover, the results showed that joint efficiency began to sharply decrease when the gap exceeded 1.6 mm. Furthermore, the thermomechanical model of varied gap FSW showed when the gap exceeded 0.8 mm, the material transferred by the tool would not completely fill the cavity formed by the pin’s forward motion. Finally, the gap-tolerance window for FSW was evaluated in terms of welding defects, joint efficiency, and thermomechanical behaviour.
  • Optimization of process parameters of metal inert gas welding with
           preheating on AISI 1018 mild steel using grey based Taguchi method
    • Abstract: Publication date: December 2019Source: Measurement, Volume 148Author(s): Sudhir Kumar, Rajender SinghAbstractWelding processes form an integral part of manufacturing industries and construction works. Among all the welding processes available, MIG welding is the widely used welding process due to its versatility and higher productivity. In this research work, AISI 1018 mild steel samples have been welded in V-butt joint configuration using MIG welding. The design of experiment is Taguchi based Orthogonal Array (L9). Effect of process parameters such as current, voltage and preheat temperature has been studied and welds are examined using X-ray radiographic tests. Weld quality has been assessed in terms of tensile properties of weldments such as ultimate tensile strength and percentage elongation. Process parameters have been optimized using grey based Taguchi methodology. Further, analysis of variance has been done to ascertain the influence of input parameters on response parameters. Experimental results show that to achieve optimum ultimate tensile strength and percentage elongation of weldments, preheat temperature turns out to be the most effective input parameter followed by welding current and voltage. A mathematical model has been developed using multiple regression equations. In the end, a confirmatory experiment with optimized parameters from the analysis has also been performed to confirm the results.
  • Metrological triangles in impedance comparisons
    • Abstract: Publication date: December 2019Source: Measurement, Volume 148Author(s): Krzysztof Musiol, Marian KampikAbstractA method for checking impedance comparison bridges, based on metrological triangles is presented in the paper. It is proved that, both in differential and ratio comparison circuits, it is possible to assess the consistency (and thus accuracy) of measurement basing on intercomparison of groups composed of at least three standards of unknown but stable values. In this paper the consistency level is defined. The triangle method was applied at various stages of construction of differential and ratio bridges. The method enabled us to detect and remove systematic errors in 1:1 bridge circuits and finally confirmed the accuracy assessed during construction of the bridges.
  • Indirect ice load monitoring and strength analysis of a steel gate
           considering uncertainties
    • Abstract: Publication date: December 2019Source: Measurement, Volume 148Author(s): Meng Zhang, Binbin Qiu, Qiang Wei, Xianqiang Qu, Dexin ShiAbstractOne of the most significant challenges in analysing steel gate strength is to obtain plausible ice loads that are exerted on the gate. The indirect monitoring of ice-induced loads is an inverse problem of structural mechanics, and various numerical models have been developed over the years for estimating ice loads with reasonable accuracy. However, the mathematical models used to estimate ice loads are usually affected by uncertainty factors such as uncertainties in the transfer matrix, which reduces the reliability of the gate strength analyses. In this study, a D-optimal design combined with a sequential exchange algorithm or C-optimal design method was used to identify 13 candidate arrangement schemes of strain gauges based on an assumption that the transfer matrix is accurate. Every candidate arrangement scheme of the strain gauges on the steel gate corresponds to a certain number of strain gauges. An experimental structure was designed, and a benchmark experiment was conducted to estimate the error of the transfer matrix—i.e., the uncertainties in the mathematical model. Monte Carlo simulations were performed to investigate the effects of the uncertainties of the mathematical model on the estimated ice loads, and the optimal strain gauge locations were then determined. Based on the optimal arrangement scheme, the upper and lower limits of the estimated ice loads corresponding to different probabilities were obtained with the structural monitoring data of a steel gate in a cold region using the Monte Carlo simulation method. Finally, the gate strength was analysed based on the upper limits of the estimated ice loads corresponding to a probability of 99.74%. The analysis results indicate that the ice load did not threaten the gate safety during the structural monitoring period.
  • ANN based angle tracking technique for shaft resolver
    • Abstract: Publication date: December 2019Source: Measurement, Volume 148Author(s): Resat CelikelAbstractShaft resolver is widely used in many industrial applications, such as robotics and machine automation applications. Because the performance of the system depends on measurement accuracy, in order to perform an accurate position control, the absolute position data measured by the shaft resolver must be nearly as error-free as possible. In this study, an Artificial Neural Network (ANN)-based measurement method was proposed to reduce the errors of the shaft position calculated by using the high-frequency signals. 3-inputs, 10-neurons in hidden layer, and 2-outputs were taken for developed ANN. The proposed method was prepared to operate in a Field Programmable Gate Array (FPGA). Simulation with FPGA hardware was performed in MATLAB/Simulink environment by using FPGA-in-the loop feature. The proposed method was compared with conventional methods. It was seen that the error rate of the proposed method was very low compared to the other methods.
  • A low-cost noise measurement device for noise mapping based on mobile
    • Abstract: Publication date: December 2019Source: Measurement, Volume 148Author(s): G. Quintero, A. Balastegui, J. RomeuAbstractFor the production of representative noise maps, a large amount of information is necessary, which includes, among others, on-site measurements of environmental noise. Thus, mobile sampling emerges as a possible solution for the enhancement of data acquisition. The present paper proposes a low-cost noise monitoring device, in order to take georeferenced mobile measurements at each 1/3 octave band (63 Hz–10 kHz). The implementation and accuracy tests of the equipment are presented. It is found, under laboratory and field tests, that the device measurement values are around ±0.5 dB of those obtained with a Class 1 sound level meter for LAeq and around ±1 dB for 1/3 octave band. Furthermore, a set of mobile measurements taken suggest that it is actually possible to perform the mobile sampling, which would improve the spatiotemporal granularity of noise measurements without compromising the accuracy, although certain requirements should be fulfilled to ensure representativeness.
  • Sacrificial copper strip sensors for sulfur corrosion detection in
           transformer oils
    • Abstract: Publication date: December 2019Source: Measurement, Volume 148Author(s): M.S. Ahmad Khiar, R.C.D. Brown, P.L. LewinAbstractExisting protocols (e.g., ASTM D 1275-B standard test method) applied to detect and monitor sulfur corrosion in transformer insulating oils are imprecise as it depends on visual observation. As a solution, thin-film sacrificial copper strips are proposed as a corrosive sulfur sensor. A two-level factorial design is utilized to investigate the significant effect of area and thickness upon the sensor’s transformation resistance values. Next, a regression model is developed to estimate the sensor’s transformation resistance values as functions of area and thickness. The resultant outputs from the two-level factorial design revealed that area, as a variable, exhibited higher significance at 90.19%, compared to either thickness or interaction between area and thickness. The proposed regression model obtained from two-level factorial design is significant in describing the trend displayed by the sensor’s transformation resistance values. Finally, this paper details the clear correlation between the sensor’s transformation resistance values and elemental sulfur concentration.
  • An ultrasound-based water-cut meter for heavy fuel oil
    • Abstract: Publication date: December 2019Source: Measurement, Volume 148Author(s): Carlos Eduardo Teixeira, Luiz Eduardo Borges da Silva, Giscard F.C. Veloso, Germano Lambert-Torres, Mateus Mendes Campos, Ismael Noronha, Erik L. Bonaldi, Levy E. Lacerda de OliveiraIn order to have on-line measurement of water content in heavy fuel oil (HFO), the so-called water-cut meters are used. Typically, measurements performed by these devices are based on capacitive principle, in which the water-in-oil emulsion acts as the insulation material. In this case, variations in the water/oil ratio affect the dielectric, which causes the capacitance to vary. By contrast, in our approach, water-in-oil emulsions act as the material medium for propagation of ultrasound waves so that the variations in water/oil ratio affect their frequency components. Since we keep the transmitter transducer excitation the same, the received ultrasound signal will vary according to the current characteristics of the fluid. As it is not known in advance which components will be affected by the presence of water, we present a methodology consisting in laboratory experiments in conjunction with Principal Component Analysis (PCA). This methodology leads to an expression that relates the score value issued from PCA and the water content information. In addition to presenting the development of an ultrasound-based water-cut meter, this paper presents some results obtained from both laboratory and field measurements. We could also compare the proposed system with a PCB-based capacitive sensor under field conditions. We verified a maximum difference of 0.2 percentage point between both approaches.Graphical abstractGraphical abstract for this article
  • A novel hybrid calibration method for FOG-based IMU
    • Abstract: Publication date: December 2019Source: Measurement, Volume 147Author(s): Bo Xu, Lianzhao Wang, Tenghui DuanAbstractFiber optic gyro inertial measurement unit (FOG-IMU) discrete calibration is a challenging task due to its dependence on non-linear filtering, complex computations, turntable accuracy and so on. In view of these problems, this paper proposes a high precision FOG hybrid grading calibration method using low-cost turntable. Combination method of coarse and accurate calibration is used to realize high precision calibration of FOG-IMU sensors. First of all, the system parameters sensors of IMU are calibrated using coarse calibration method. The parameters of accelerometer and gyro biases are calibrated by using low-cost turntable. In addition, the effect of the lever-arm is also considered. Then, system parameters are compensated. Afterwards, the residual components of IMU system parameter calibration are taken as estimated objects. According to the basic error equations of inertial navigation algorithm, 27-dimensions Kalman filter is formed based on velocity errors observations, and calibration path is arranged reasonably. Finally, the residual error of coarse calibration is estimated and modified, accordingly. The proposed method is validated through simulation and experiment with various rotation rates. The results verify the feasibility and effectiveness of the algorithm.
  • Low voltage smart meter for monitoring of power quality disturbances
           applied in smart grid
    • Abstract: Publication date: December 2019Source: Measurement, Volume 147Author(s): Wilson L. Rodrigues Junior, Fabbio A.S. Borges, Artur F. da S. Veloso, Ricardo de A.L. Rabêlo, Joel J.P.C. RodriguesAbstractThe large amounts of data collected by smart meters (SM), such as electric energy, water gas consumption and power quality (PQ) metrics, can create a massive flow of data transmitted between consumers and utilities. In this context, an edge-fog-cloud architecture based on a low-cost SM is proposed. The employed SM acquires voltage and current signals to obtain their frequency and amplitude, allowing PQ to be monitored through methods of detection and classification of disturbances in order to send only information about the detected disturbances to the utility, thus reducing network traffic associated with PQ disturbances in Smart Grids. The proposed methodology was embedded at a low-cost SM to enable data exchange with the utility, offering an enormous potential for real scenarios.
  • Measurement investigations in tubular structures health monitoring via
           ultrasonic guided waves: A case of study
    • Abstract: Publication date: December 2019Source: Measurement, Volume 147Author(s): Slah Yaacoubi, Mahjoub El Mountassir, Morgan Ferrari, Fethi DahmeneAbstractThis paper deals with the health monitoring of tubular structures by means of Ultrasonic Guided Waves (UGW) technique. It investigates mainly the stability of measurements, which is a key topic in Structural Health Monitoring. A corrosion-like defect is machined in a full-scale tube and then its size is increased in five steps. Their cross-section areas (CSA) go from less than 1% to around 4.5%. To get a high accuracy, a 3D laser scanner was used to measure these CSAs. The influence of the probe/tube adhesion quality on defect detectability is investigated. Propagation mode type and central frequency are also taken into account. Environmental and operational conditions variations (EOC) are studied too. Regarding the obtained results, it can be concluded that the UGW are an efficient technique for the monitoring of tubes. However, to reach a high-performance level, statistical algorithms are needed to face the problem of EOC and then manage false alarms as reliable as possible. Furthermore, to make data more stable, special care should be paid to the implementation of the sensor, such as glue durability, bonding issues, etc.
  • Preliminarily experimental research on local pressure loss of fresh
           concrete during pumping
    • Abstract: Publication date: December 2019Source: Measurement, Volume 147Author(s): Jian Chen, Haibo Xie, Jie Guo, Bin Chen, Feng LiuAbstractThe pressure of the fresh concrete during pumping in conveying pipes is critical in both concrete pump design and conveying pipes layout. The local pressure loss occurring at the connections between pipes, which often has been overlooked in the total pumping pressure research, is quite significant compared to the total pressure drop, especially for long conveying pipes. In this study, strain gauge based method was applied to measure the pressure drop at the connections of concrete during pumping. In this method, the strain gauges were calibrated by water pressure to obtain the correlation between the strain and pressure. An empirical equation for predicting the local pressure loss was also proposed and validated based on the experimental data. The results indicated that the pressure loss per pipe connection for general grades of concrete is within 0.01–0.045 MPa when the pumping rate ranges from 40 m3/h to 80 m3/h.
  • Weld bead penetration state recognition in GMAW process based on a central
           auditory perception model
    • Abstract: Publication date: December 2019Source: Measurement, Volume 147Author(s): Qisheng Wang, Yanfeng Gao, Linran Huang, Yanfeng Gong, Jianhua XiaoAbstractArc sound signals contain abundant information about the welding process, so they are widely adopted to monitor the penetration states of weld bead online. However, the arc sounds are vulnerable to back ground noises, which limits the practical application of them in industry. In this study, a central auditory perception model was proposed. This model through simulating human auditory system to identify the penetration states of weld bead in GMAW process. Firstly, the auditory spectrums of the arc sounds are obtained through auditory peripheral model. Then the shape of auditory spectrums is analyzed by an auditory cortex model. Finally, according to the auditory cortical response, character vectors are built and used to identify the penetration states. The results show that the proposed method has a high accuracy rate in the identification of penetration states of weld bead. This research provides a new method for the online monitoring of welding quality.
  • All-circular hole microstructured fiber with ultra-high birefringence and
           reduced confinement loss
    • Abstract: Publication date: December 2019Source: Measurement, Volume 147Author(s): Siraj Sidhik, Jijo V. Ittiarah, Mrinmay Pal, Tarun Kumar GangopadhyayAbstractAll-circular hole microstructured fiber with ultra high birefringence in the order of ∼10−2 with reduced confinement loss is proposed. The increased birefringence is achieved by introducing an axial anisotropy in the geometry of the fiber, using a modified arrangement of circular holes. The vital properties of the microstructure fiber like birefringence, confinement loss, dispersion and walk-off parameter has been studied by employing numerical solution through finite element method. These finding should be useful for the fabrication of the proposed microstructure optical fiber.
  • Developing a Long Short-Term Memory-based signal processing method for
           Coriolis mass flowmeter
    • Abstract: Publication date: December 2019Source: Measurement, Volume 148Author(s): Yanjin Zhang, Yajun Liu, Zhendong Liu, Weiping LiangAbstractCoriolis mass flowmeter is widely used in various fields due to its high accuracy, but it still needs to be improved in some special conditions. This paper proposes a deep learning-based signal processing method for Coriolis mass flowmeter. Firstly, we set up an experimental platform to collect data, taking the vibration signal as the input feature and the mass flow as the sample label. Secondly, we designed networks with different structures (including LSTM, RNN and ANN) and adopted batch normalization to speed up convergence. Finally, Bayesian model fusion and moving average were used to reduce generalization error. Experiment results prove that the model with LSTM layer is better than other single models and the mean square error of the optimized model reduces to 0.0047, which is far superior to the calibrated meter (0.1200). These findings that get rid of traditional methods are expected to break through existing bottlenecks.
  • Development of termite detection system based on acoustic and temperature
    • Abstract: Publication date: December 2019Source: Measurement, Volume 147Author(s): Muhammad Achirul Nanda, Kudang Boro Seminar, Dodi Nandika, Akhiruddin MadduAbstractThe subterranean termite, belonging to the genus Coptotermes, is the pest that causes maximum destruction in wooden structures, forest trees and crops. Owing to its aggressiveness and hidden existence, it is difficult to visually determine whether a termite infestation is active and damage is occurring. Consequently, the development of a termite detection system as a critical component of termite pest control systems is necessary. A novel termite detection system was developed based on acoustic and temperature signals. The system has two capabilities: it can detect the presence of termites and estimate the population size. In this study, a support vector classification (SVc) and artificial neural network (ANN) algorithm were applied to recognize the termites’ signals. After optimizing various input types, kernel functions and model parameters, a robust model was successfully constructed with a specific capability, i.e., a SVc model for detecting termites and ANN model for estimating the termite population. Based on the performance assessment, the proposed termite detection system can detect the presence of termites with an accuracy of 93.83% and estimate their population with a root mean square error (RMSE) of 123.828. The results of our study indicated that the embedded models in the proposed termite detection system successfully proved the feasibility of detecting the presence of termites and simultaneously estimating the size of their population.
  • The characteristics of dynamic fracture toughness and energy release rate
           of rock under impact
    • Abstract: Publication date: December 2019Source: Measurement, Volume 147Author(s): Peng Ying, Zheming Zhu, Fei Wang, Meng Wang, Caoyuan Niu, Lei ZhouAbstractTo investigate the characteristics of rock fracture toughness and dynamic energy release rate, impact experiments were conducted in large single cleavage semicircle compression (LSCSC) specimens. Fracture toughness and energy release rate of three sandstones were investigated and a drop-weight device was applied. Crack length and crack propagation velocity were corrected by fractal method, and fracture surface morphology was obtained by scanning electron microscope. The dynamic stress intensity factor (DSIF) was acquired from the finite element model established in the ABAQUS. The DSIF history was acquired, and the initiation and propagation toughness were determined according to the measuring result of fracture time. It shows that, for a material, propagation toughness is related to its Young’s modulus, and the higher the Young’s modulus or wave impedance is, the larger the propagation toughness is. For black sandstone, the energy release rate increases rapidly with crack length, whereas for green and red sandstones, it increases slightly under a same speed impact.
  • Electromagnetic field evaluation and EMI on board during a marine
           geophysical data acquisition (COSMEI)
    • Abstract: Publication date: December 2019Source: Measurement, Volume 147Author(s): Vincenzo Di Fiore, Michele Punzo, Nicola Pelosi, Paolo Scotto di Vettimo, Michele Iavarone, Francesca Budillon, Giovanni Zeni, Fabrizio LirerAbstractWhen performing oceanography measurements, it is critical to assess the presence of the noise sources that could affect the measured data and lead to wrong interpretation of the results. This paper report the result of an oceanography survey conducted by ISMAR-CNR, Naples, in the north-eastern marine sector of the Ischia Island and assess the influence of EMI on the measured results. The analyzed measurements of the Electric and Magnetic fields showed values of the E up to 0.82 V/m and of B up to 85 μT. By assuming a standard conductor, an inductance L up to 47 Ω on the cable corresponding to an induced electromotive force of 1184 mV was calculated. Also the experimental data show the EMI increase in site where the Pearson index correlation is higher.The results demonstrate that in an oceanographic survey planning, a preliminary electromagnetic screening is advisable to optimize the measurement setup.
  • An accurate detection method for surface defects of complex components
           based on support vector machine and spreading algorithm
    • Abstract: Publication date: December 2019Source: Measurement, Volume 147Author(s): Zhiyuan Wang, Dahu ZhuAbstractDetecting the surface defects of complex components exhibiting different visual properties in positions, shapes, number and sizes is a challenging problem. In this paper a novel computational framework is developed to accurately detect the component surface defects through three steps. In the framework, the positions and shapes of the components surface defects are extracted based on the support vector machine and the point cloud model. Then a novel unsupervised classification method termed as spreading algorithm is proposed to classify the defects for the recognition of the number of defects, and finally the sizes of defects are calculated using the covariance matrix 3D measurement method. Experimental cases on two typical complex components, the blade with depression and protrusion defects and the transmission case with defect and normal features, are investigated. The results are particularly compared with the ones with the state-of-the-art methods, showing the practicality and effectiveness of the proposed technique.
  • Research and optimization of intelligent diagnosis algorithm based on rope
    • Abstract: Publication date: December 2019Source: Measurement, Volume 147Author(s): Juan Wu, Shuai Huang, Ziming KouAbstractFor less monitor and poor performance in the intelligence of the existing fault diagnosis system based on wire rope tension, an optimized intelligent diagnosis algorithm is proposed to diagnose the faults. These faults are difficult to monitor in the past, such as blocked cage, over-wind and slipped rope. Selecting the radial basis function (RBF) as the kernel function, two parameters of penalty factor and radial basis kernel parameter in the least squares support vector machine (LSSVM) are further optimized by artificial bee colony (ABC) algorithm. The results show that the LSSVM algorithm does not need a large number of original data, and has no overfitting and generalization ability. The prediction accuracy and the mean square error of the ABC-LSSVM algorithm are improved. It shows better pattern recognition performance, which can be used as a kind of intelligent diagnosis algorithm for the design of the rope tension fault diagnosis system.
  • On-chip order tracking method using wireless sensor networks based on
           hardware cross-layer design
    • Abstract: Publication date: December 2019Source: Measurement, Volume 147Author(s): Xin Xiao, Lei Deng, Baoping Tang, Yan HanAbstractOrder-tracking technique is widely accepted to account for speed variation. Meanwhile, Wireless Sensor Networks (WSNs) is highly focused since the nodes can collect vibration data in special applications. Thus, it’s meaningful to realize order-tracking using WSNs. In this paper, a novel on-chip order tracking method using WSNs based on hardware cross-layer design is proposed, in which the vibration data can be sampled with uniform angle on chip. First, a high performance WSNs system based on dual-core architecture is developed to monitor shaft angle and machine vibration, and hardware cross-layer design is researched to send key-phase pulse with low delay jitter. Second, a data sampling control method is established to realize on-chip uniform angle sampling. Finally, the performance of the proposed on-chip order tracking method is verified by some experiments.
  • Evaluation of synthetic gas harmful effects created at the underground
           coal gasification process realized in laboratory conditions
    • Abstract: Publication date: December 2019Source: Measurement, Volume 147Author(s): Milan Durdán, Marek Laciak, Ján Kačur, Patrik Flegner, Karol KostúrAbstractUnderground coal gasification (UCG) is an industrial process that provides an alternative to conventional underground mining at coal seams that are located especially deep underground. This process converts coal into product gas (syngas). The product gas composition depends on the coal geology and the gasification parameters. The coal (coal seam) and oxidant (a mixture of the oxygen and air) are input to the gasification process, and their valid combination should provide better conditions of gasification. The fracturing, cracks and also operating failures occur inside the gasification zone and surrounding rocks during the underground coal gasification process as the underground coal cavity evolves. There was only a little research focused on their effects to date, although these causes directly affect the gasification efficiency and have the environmental impacts. The paper describes the analysis of the harmful impact of the produced gas on the vulnerable area in terms of possible poisoning and potential explosion by using a mathematical model for mixing gasses. The analysis is performed using four laboratory experiments realized on two gasifiers. The harmful effects of the produced gas are compared for the different gasification method of the individual experiments by taking into account the low and high heat capacity obtained. The obtained heat capacity is determined by a mathematical model for the heat balance of the output components.
  • A new bi-level data envelopment analysis model for efficiency measurement
           and target setting
    • Abstract: Publication date: December 2019Source: Measurement, Volume 147Author(s): Seyed Hossein Razavi Hajiagha, Hannan Amoozad Mahdiraji, Madjid TavanaAbstractData envelopment analysis (DEA) is a well-known and widely used method for performance evaluation in a set of homogeneous units. We propose a new bi-level DEA model for efficiency measurement and target setting. The fundamental novelty of the proposed model is threefold. We: (1) set both efficiency and profit concurrently as targets; (2) limit the amount of changes in the inputs and outputs to prevent unachievable targets; and (3) predict some targets for efficient units beyond the inefficient ones. We present a case study in the banking industry to demonstrate the efficacy of efficiency measurement and target setting in the proposed models.
  • Particle swarm optimization-based energy efficient target tracking in
           wireless sensor network
    • Abstract: Publication date: December 2019Source: Measurement, Volume 147Author(s): J. Rejina Parvin, C. VasanthanayakiAbstractWireless Sensor Network plays a vital role in tracking the mobility of targets like animals for habitat monitoring, vehicle monitoring etc. Many researches have been carried out for the precise identity of the target. In this research work, a distributed energy optimization method for target tracking is carried out using Particle Swarm Optimization. The proposed work is comprised of estimation phase and prediction phase. Here, clustering is performed using maximum entropy method. Grid exclusion is used for the coverage of nodes in the network. Performance evaluation is carried out for the proposed target tracking method with the existing systems using network simulator software.
  • A temperature-independent optical voltage transformer based on FBG-PZT for
           13.8 kV distribution lines
    • Abstract: Publication date: December 2019Source: Measurement, Volume 147Author(s): Marceli Nunes Gonçalves, Marcelo Martins WerneckAbstractInstrument Optical Voltage Transformers (OVTs) have been presented by the electric power industry as an alternative to the conventional iron and copper inductive instrument transformers from the last years. OVTs based on fiber Bragg gratings and piezoelectric (PZT) crystals present two well know limitations: maximum voltage that can be applied on the PZT due to their limited electric field and the cross-sensitivity of the FBG on temperature that influence measurement accuracy. This paper presents an FBG-PZT based OVT with a novel thermally compensated method, capable to measure and monitor distribution voltages of 13.8 kV class. The presented results show that the developed system satisfies the 0.2 Accuracy Class of IEC standards, meaning a 0.2% accuracy.
  • Evaluation of synthetically generated patterns for image-based 3D
           reconstruction of texture-less objects
    • Abstract: Publication date: December 2019Source: Measurement, Volume 147Author(s): Željko Santoši, Igor Budak, Vesna Stojaković, Mario Šokac, Đorđe VukelićAbstractEvery material and every surface has its own visual texture. Surfaces with monotone, repetitive or uniform visual texture represent a challenge for the image-based Structure From Motion Multi-View Stereo three-dimensional (3D) reconstruction method. It is possible to overcome the lack of visual texture on the surfaces by projecting synthetically generated images (patterns) using a video projector. This research proposes the generation of the synthetic images that are based on digits of irrational numbers pi, phi, e, sqrt2, sqrt3 and digits produced by the random number generator. Images were divided into three classes based on the number of hues. The aim is to evaluate synthetically generated images and determine the characteristics of the most suitable synthetic image(s) that increase the accuracy of the final reconstructed polygonal 3D model. The synthetically generated images were evaluated using results of the multi-criteria analysis as well as real and virtual planar surface 3D digitization methods, where images with uniform distribution histogram have the most suitable characteristics. To verify evaluation results, 3D reconstruction of aluminium test model was carried out. Four polygonal 3D models of the aluminium test model were reconstructed. Three polygonal 3D models were reconstructed using projected patterns of each class, and one was reconstructed in daylight condition. The resulting accuracies of reconstructed polygonal 3D models were evaluated using the Computer-Aided Inspection. The polygonal 3D model obtained by projecting class I pi I pattern with the strong random stochastic visual texture achieved std. distance of 0.173 mm and mean distance of 0.016 mm compared to the polygonal 3D model obtained in daylight condition with std. and mean distance of 1.188 mm and −0.139 mm respectively.
  • Investigation into coaxial cable Fabry–Perot interferometers for strain
           measurement and crack detection in RC structures
    • Abstract: Publication date: December 2019Source: Measurement, Volume 147Author(s): Tong Jiao, Zhi Zhou, Hai XiaoAbstractThe coaxial cable Fabry–Perot interferometer (CCFPI) sensor is a promising technology for structural health monitoring, especially for large strain measurements. This study aimed to explore the possibilities of applying this technique to the strain measurement and crack detection in RC structures. First, a distributed CCFPI sensing system was developed that was used for signal processing and data collection. Subsequently, four- and three-point bending tests were carried out on RC specimens. In the tests, separate methods were proposed for fabrication, encapsulation, and installation of a CCFPI sensor on RC structures. The CCFPI sensors were separately adhered to the rebar, embedded within the concrete volume as well as bonded at the bottom surface of the test specimen, and their performance regarding distributed strain measurements, crack detection, and quantification, was investigated. Findings from the tests have demonstrated that CCFPI sensors can measure the developed strains from the initial loading, cracking, and from the yielding to the crashing of the RC structures. Some systematic errors resulting from calibration were observed in the quantitative comparative data, and accurate calibration is crucial to improve the measurement accuracy. The results also exhibit the capability of CCFPI sensors for crack detection and crack width determination.
  • Prediction of mechanical properties of rubberised concrete exposed to
           elevated temperature using ANN
    • Abstract: Publication date: December 2019Source: Measurement, Volume 147Author(s): Trilok Gupta, K.A. Patel, Salman Siddique, Ravi K. Sharma, Sandeep ChaudharyAbstractConsidering scarcity of natural sand, waste rubber tyre can be an alternate ingredient for replacement of conventional fine aggregates in the production of concrete. Use of the waste rubber tyre in building materials is beneficial from sustainable and economical points of view. A systematic and comprehensive experimental study was conducted earlier by the authors for the mechanical and durable properties of rubberised concrete subjected to elevated temperature. However, there is non-availability of a mathematical model for rapid prediction of mechanical properties of the rubberised concrete subjected to elevated temperature. To bridge this gap an attempt has been made for development of explicit expressions through artificial neural network (ANN) approach in this paper. The training, validation, and testing data sets for ANN, are compiled from the recent researches of the authors. The input data sets contain six levels of elevated temperature (T) with three exposure durations (t) for all the specimens having six different fiber content (RF) along with three different water-cement ratio (w/c). On the other hand, the output parameters consist of mechanical properties (compressive strength static modulus of elasticity, dynamic modulus of elasticity and mass loss). Sensitivity analysis has also been carried out to investigate the effect of the input parameters on the output parameters. It is found that the average contribution of w/c,RF,T,t to all the output parameter is 6.67%, 10.10%, 80.01% and 3.22% respectively. The parameter T has highest impact on the all output parameters followed by RF whereas, rest of the input parameters (w/c,t) have relatively lower impact.
  • Integration and test of piezocomposite sensors for structure health
           monitoring in aerospace
    • Abstract: Publication date: December 2019Source: Measurement, Volume 147Author(s): Filip Ksica, Zdenek Hadas, Jiri HlinkaAbstractThe paper presents an innovative approach for Structure Health Monitoring utilizing piezocomposite plates as active sensors. The present work is motivated by the increasing interest in reduction of maintenance costs for aircrafts, which can be achieved by implementing self-sufficient sensor networks into the aircraft to predict risk states and prevent structural failures. These networks could supplement and possibly replace the expensive maintenance inspections. Piezoelectric materials have recently been under a rapid development, have been utilized in various fields of industry and due to their inexpensive and robust nature they can be used as sensors in non-intrusive Structure Health Monitoring networks. The presented approach uses piezocomposite sensors embedded into the structure of a small civil aircraft to directly measure structural vibrations. The functionality of the entire measurement chain was tested during an experimental flight, the acquired data will be used for further research of data-processing, impact detection and structure health prediction.
  • Correlation of solar power prediction considering the nominal operating
           cell temperature under partial shading effect
    • Abstract: Publication date: December 2019Source: Measurement, Volume 147Author(s): Pedram Asef, Ramon Bargallo, A.E. Hartavi Karci, Payam Niknejad, M.R. Barzegaran, Andrew C. LapthornAbstractThe steadily rising efficiency together with the accuracy of prediction in solar photovoltaic (PV) energy requires a deterministic reliability in the realistic PV characteristic’s prediction subject to climatic changes. This empirical-based research validates IEC 61853 and improves output power prediction of a solar PV module with considering nominal operating cell temperature (NOCT) using online infrared thermal camera at short range outside. The impact of NOCT consideration is investigated, in which the error can be as high as 10.4 °C in comparison to non-NOCT. The objective is minimizing the power prediction error for the PV module, the significant parameters of the maximum power point tracking (MPPT) controller are used to evaluate the changes followed by the climatic-related parameters under partial shading condition. A set of non-parametric correlations are calculated using Spearman’s ρ and Kendall τ rank statistical methods to avoid experimental measurement difficulties and cost for an advanced output power prediction. Finally, the differences on the heat distribution of each cell, and its impact in the annual power prediction have been numerically and experimentally verified.
  • Collaborative target tracking of IoT heterogeneous nodes
    • Abstract: Publication date: December 2019Source: Measurement, Volume 147Author(s): Xu Lu, Jun Liu, Huimin ZhaoAbstractA sensing system consisting of a single type of sensor has numerous defects in target tracking, for example, RFID sensor network has a limited positioning accuracy and camera sensor network has a large data communication. Thus, the target tracking of heterogeneous nodes has become the present research focus. Three types of sensor nodes, namely, RFID, camera, and passive sensors, were combined in this study for fusion of heterogeneous node data. Moreover, a target tracking algorithm of heterogeneous nodes was proposed. The proposed algorithm constructed a node sensing efficacy function through particle filtering, built a sensing energy efficiency function by balancing surplus node energies, and eliminated members in the perception group that participate in the target tracking process. Experimental results indicate that in comparison with existing algorithms, the proposed algorithm has high target tracking accuracy and has reached a favorable balance with regard to tracking accuracy and network energy consumption.
  • Energy-efficient data gathering algorithm relying on compressive sensing
           in lossy WSNs
    • Abstract: Publication date: December 2019Source: Measurement, Volume 147Author(s): Ce Zhang, Ou Li, Yanping Yang, Guangyi Liu, Xin TongAbstractPacket loss is one of the most critical factors affecting the accuracy of compressed sensing (CS)-based data gathering algorithms. In this paper, a data gathering algorithm is proposed to decrease energy consumption and resist packet loss. Each cluster head formulates a sparsest random measurement matrix (SRMM) via the received data to avoid the measurement of the lost node and decrease the number of measurements. To employ spatial correlation between clusters, the sink constructs a block diagonal matrix (BDM) as a measurement matrix via SRMMs and reconstructs the entire network data. Additionally, the optimal number of clusters is discussed under this framework to reach the minimum power consumption. The SR-BDM is evaluated on the emulated data and the real sensor data from GreenOrbs, respectively. The simulation results indicate the proposed algorithm reaches high precision, both with reliable links and with a 60% packet loss rate link, without causing increased energy consumption.
  • Rapid evaluation of coaxiality of shaft parts based on double maximum
           material requirements
    • Abstract: Publication date: December 2019Source: Measurement, Volume 147Author(s): Zhemin Tang, Meifa Huang, Yonghou Sun, Yanru Zhong, Yuchu QinAbstractSimultaneous application of the maximum material requirements on the datum and coaxiality tolerances (referred to as DMMR coaxiality) of shaft parts can ensure assembly and reduce costs. Existing DMMR coaxiality evaluations use either inflexible real functional gauges or slow mathematical methods, which limits the applications of such a good tolerance in industry. This paper investigated a fast mathematical evaluation method for DMMR coaxiality. First, according to ISO requirements, the geometry and utility of the real functional gauge were analyzed. Then, an adaptive virtual gauge (AVG) was established, and the geometric structure and motion of the AVG were analyzed. After that, the mathematical evaluation method of the DMMR coaxiality tolerance was provided with uncertainty analysis. Finally, an exemplary application on a stepped shaft was presented, and the accuracy and speed of the method were reflected and improved by comparison with existing methods.
  • Quantitative texture measurement of gray-scale images: Fractal dimension
           using an improved differential box counting method
    • Abstract: Publication date: December 2019Source: Measurement, Volume 147Author(s): Chinmaya Panigrahy, Ayan Seal, Nihar Kumar MahatoAbstractTexture analysis methods have been used in various image processing applications, such as segmentation, classification, and recognition, shape analysis. The performance of computer vision and image processing algorithms depend on visual texture patterns. However, it is difficult to define. Fractal Dimension (FD) helps to measure the level of roughness present in an image. A significant amount of work is available in literature to measure FD. Differential Box Counting (DBC) is one such successful method exploited in image texture analysis study, because it is simple and easy to understand. DBC is modified several times to yield a better FD value. However, most of the state-of-the-art methods suffer from the over-counting and under-counting of boxes, larger box-height, less number of grid sizes, inappropriate line fitting method. This work introduces a gray-level shift-invariant DBC method, which uses a new formula for counting boxes along z-direction to solve over-counting of boxes, a partitioning-shifting-partitioning mechanism to fix under-counting of boxes along xy-direction, a smaller box-height to enhance the FD value and robust least squares regression to estimate a line accurately. All the experiments are performed on synthesized Fractal Brownian Motion image dataset and four real datasets. The obtained results illustrate that the proposed DBC method outperforms state-of-the-art DBC methods.
  • Research on an enhanced scale morphological-hat product filtering in
           incipient fault detection of rolling element bearings
    • Abstract: Publication date: December 2019Source: Measurement, Volume 147Author(s): Xiaoan Yan, Ying Liu, Minping JiaAbstractIncipient vibration signals of rolling element bearing are usually characterized by weak fault symptoms and multiple interference source components, which imply that it is difficult to recognize effectively the defects of rolling element bearing at an early stage. To address the issue, a novel early fault detection strategy based on an enhanced scale morphological-hat product filtering (ESMHPF) is proposed in this paper. Firstly, motivated by the existing morphology theory, the concept of morphology-hat product operation (MHPO) is presented to handle the collected weak fault signal, which can extract efficiently periodic impulse characteristics closely linked to the bearing defects. Subsequently, diagonal slice spectra (DSS) are incorporated into morphological analysis, which can achieve the efficacy of noise rejection and feature enhancement. Ultimately, the optimal scale morphological filtering results are determined by using a sensitive index termed as fault feature ratio (FFR) for identifying weak damage feature and completing early fault detection. Simulated signal and two experimental cases of run-to-failure are performed to assess the efficacy of the proposed algorithm. The analysis results achieved show that the formulated algorithm can identify clearly early fault symptoms immersed in bearing vibration data. Moreover, the availability of superiority of our designed approach is demonstrated by comparing with traditional multiscale morphological filtering and some existing algorithm. This study provides a new idea for the improvement of incipient damage identification of rolling element bearings.
  • Multi-technical characterization of Roman mortars from Complutum, Spain
    • Abstract: Publication date: December 2019Source: Measurement, Volume 147Author(s): Duygu Ergenç, Rafael FortThis paper provides a multi-technical characterization of mortar samples from the Roman city Complutum. It aims to contribute to future conservation projects as well as archaeological research on Roman construction techniques. Archaeological mortar samples were analysed via binder aggregate ratio, grain size distribution and POM, XRD, SEM/EDS, TGA/DSC, XRF and isotope analysis (δ18O and δ13C). The analyses provided information on how mortar was prepared by Roman builders. Sub-rounded sand aggregates collected from Henares riverbank and Tertiary-age limestone were used in lime production. To make the mortar hydraulic, ceramic dust, fly ash, chamotte, and charcoal were used. Generally, a planned and consistent mortar manufacture can be deduced. In two construction phases there exist slight differences in mortar production. In the second phase more aggregate were preferred after empirical knowledge gained about crack formation. The combined measurement techniques utilized in this study permitted relative dating of the mortar based on compositional types.Graphical abstractGraphical abstract for this article
  • Direct temperature measurement via thermocouples within an SPS/FAST
           graphite tool
    • Abstract: Publication date: December 2019Source: Measurement, Volume 147Author(s): M. Radajewski, S. Decker, L. KrügerAbstractMany publications investigate temperature distributions by simulations. Temperature is often not practically measured or only at a few locations inside the sintering tool using thermocouples. However, thermocouple temperature measurement is very sensitive to environmental conditions and can be extremely defective. This study investigates the feasibility of thermocouple temperature measurement at different measuring positions within a graphite tool during SPS/FAST. Three different graphite tool setups and three different thermocouples were used for the temperature measurements. The thermocouples were covered by an Al2O3 tube and placed directly inside a borehole in the setup. Process temperatures, measured by a vertical pyrometer, up to 1200 °C were realized. Experimental data at different temperature plateaus show significant temperature differences depending on the applied thermocouple and tool setup. It is shown that the temperature present is underestimated by the thermocouple and measuring errors vary drastically with the thermocouple length, which is inserted in the sintering tool.
  • Characterization of vibration relative amplitude in direct detection
           Φ-OTDR using variable gain method
    • Abstract: Publication date: December 2019Source: Measurement, Volume 147Author(s): Xin Liu, Yu Wang, Jie Zou, Pengfei Wang, Qing Bai, Dong Wang, Mingjiang Zhang, Hongjuan Zhang, Baoquan JinAbstractVibration relative amplitude characterization has always been a tough problem in direct detection phase-sensitive optical time-domain reflectometry (Φ-OTDR) system due to the nonlinear relationship between the optical intensity and vibration amplitude. In this paper, a novel variable gain method is proposed to characterize the relative amplitude of external vibration. The mathematical model of Φ-OTDR is established, and the influence of external vibration on detected coherent Rayleigh back-scattering light in a single-mode fiber is simulated. Then, the vibration signals of different amplitudes imposed on the sensing fiber are further investigated, and the relationship between the interference amplitude peak power and vibration amplitude is derived. On the basis of the theoretical analysis, the variable gain method is carried out and implemented in Φ-OTDR system. The experimental results demonstrate that the calibrated interference peak power increases linearly with the applied vibration amplitude, and a high correlation coefficient (R2 = 0.93071) for linear fitting is obtained.
  • Prediction of blast induced ground vibration (BIGV) of quarry mining using
           hybrid genetic algorithm optimized artificial neural network
    • Abstract: Publication date: December 2019Source: Measurement, Volume 147Author(s): Yousef Azimi, Seyed Hasan Khoshrou, Morteza OsanlooAbstractEfficient prediction of Open Pit mining blast induced ground vibration, has an important role in reduction of the environmental complaints. This paper proposed a new hybrid evolutionary artificial neural network (ANN) optimized by genetic algorithm (GA) to predict peak particle velocity (PPV). The proposed GA-ANN suggests a systematic and automated way to find out a proper ANN architecture namely; number of neurons, activation functions, training algorithm and number of epochs. A data set consisting of maximum charge weight per delay, horizontal distance (HD), radial distance (RD) and a new modified radial distance (MRD) between monitoring and blasting station provided at Sungun Copper Mine site in Iran were used to validate the proposed approach. Comparing the performance of the proposed GA-ANN model by statistical indices indicate the superiority of the GA-ANN model against the empirical predictors and neuro-fuzzy inference system. As an important finding, incorporating MRD instead of the conventional distance measures of HD and RD improves the accuracy of the prediction. Finally results signify the efficiency of the proposed GA-ANN approach in finding optimum architecture of ANN while trying to predict PPV.
  • Analysis of leakage current characteristics during aging process of SiR
    • Abstract: Publication date: December 2019Source: Measurement, Volume 147Author(s): Jaber Dadashizadeh Samakosh, Mohammad MirzaieAbstractThis paper presents the comprehensive analysis of Leakage Current (LC) of a silicone rubber insulator under uniform and longitudinal non-uniform pollution conditions based on a large amount of test data. The experimental tests are carried out under different humidity levels for un-aged and aged samples. The results obtained indicate that the LC harmonics magnitudes increase with increasing the salt deposit density, aging time, and humidity, while they decrease with increasing the pollution non-uniformity degree. The analysis of phase angle difference between LC and applied voltage (θI-V°) demonstrates that the θI-V° is in the range of 54.3°–60.4°, 20.1°–32.5°, and 7.5°–11.8° under clean condition, light pollution and moderate pollution conditions, respectively. In addition, the θI-V° is less than 2.3° under heavy pollution condition. The non-uniformity of pollution distribution and insulator aging time have very little effect on the θI-V°, while the increase of humidity leads to a slight decrease in the θI-V°.
  • Fabrication of graphene/azobenzene-perylene diimide derivative modified
           electrochemical sensors for the dopamine detection based on full factorial
           experimental design
    • Abstract: Publication date: December 2019Source: Measurement, Volume 147Author(s): Tuğba Ören Varol, Benay Perk, Okan Avci, Oğuz Akpolat, Özgül Hakli, Chenming Xue, Quan Li, Ülkü AnikAbstractIn this study, carbon paste electrode (CPE) was modified with graphene and a novel azobenzene-perylene diimide derivative (P4SAc) and utilized for the dopamine detection. Electrochemical performances of modified electrochemical platforms were examined and graphene/P4SAc/CPE exhibited the highest increment in dopamine oxidation signal. Experimental parameters were optimized by using full factorial design and analytical characteristics were examined. As a result, a linear range was obtained in the concentration range of 5–100 µM with a detection limit of 0.26 µM (n = 3). The developed sensor was also applied for the dopamine detection in injection samples and very promising results were obtained.
  • Scale-free PSO for in-run and infield inertial sensor calibration
    • Abstract: Publication date: December 2019Source: Measurement, Volume 147Author(s): Shashi Poddar, Amod KumarAbstractInertial sensor calibration is one of the most important aspects of estimating motion using an inertial navigation system. The traditional calibration technique requires mounting of sensor in different orientations using costly equipment which are not available many a times for calibrating low cost MEMS sensors. The infield calibration scheme helps in obtaining the calibration parameters directly by minimizing a multi-dimensional cost function built around principles that these sensors follow. In this paper, a novel in-run calibration algorithm is proposed that does not require the sensor to be mounted in specific orientations. This scheme updates calibration parameter even without dismounting it from its location. In this work particle swarm optimization technique with scale free network is compared with other PSO variants and recommended to be used for inertial sensor calibration. The proposed in-run calibration scheme is run on simulated and real world dataset to investigate its efficacy on uncalibrated sensor readings.
  • A novel therapeutic instrument using an ultrasound-light-emitting diode
           with an adjustable telephoto lens for suppression of tumor cell
    • Abstract: Publication date: December 2019Source: Measurement, Volume 147Author(s): Hojong Choi, Jae-Myung Ryu, Se-woon ChoeAbstractA new therapeutic instrument using ultrasound and a light-emitting diode with an adjustable optical lens was introduced for suppressing HeLa cell proliferation. A focused-type ultrasonic transducer can transmit an acoustic signal to focus the ultrasound signal onto a certain spot. Likewise, the light-emitting diode light is noncoherent and divergent, and therefore, a telephoto lens is also needed to focus light on certain desired areas. This combinational instrument, which provides an adjustable focus for the transmitted light, could be useful for differentiating the treatment and nontreatment ranges when utilizing light-emitting diodes and ultrasound sources as treatment devices. The telephoto lens can provide an adjustable illumination area of 7.06 mm × 4.01 mm and 14.05 mm × 11.67 mm in focus and defocus modes, respectively, and ultrasound can also provide adjustable acoustic beam diameters of 7 mm and 14 mm at the −6 dB intensity levels, respectively. The developed therapeutic instrument was tested to demonstrate that HeLa cell proliferation was suppressed with the ultrasound-light-emitting diode controlled by a telephoto lens. Owing to the mechanical and thermal effects caused by the ultrasound and light-emitting diode, the control of cell density by focused and defocused beams on Day 2 is shown as 99.38 ± 0.32%, 51.33 ± 10.89%, and 37.70 ± 1.95%, respectively. Therefore, we confirm that the developed ultrasound-light-emitting diode with an adjustable telephoto lens can suppress the proliferation of HeLa cells.
  • Acoustic guided wave techniques for detecting corrosion damage of
           electrical grounding rods
    • Abstract: Publication date: December 2019Source: Measurement, Volume 147Author(s): Junhui Zhao, Nicholas Durham, Karim Abdel-Hadi, Colin Aird McKenzie, Douglas J. ThomsonDetermining the integrity of grounding electrodes is challenging and there is need to augment expensive and time consuming excavation based methods. In this work pulse-echo methods based on acoustic guided waves were tested on model ground rods with machined model corrosion pits. The generation and propagation of the guided acoustic waves in the model grounding rods using different types of acoustic wave emitters and sensors was studied. The existence of three principle wave modes, longitudinal, flexural and torsional modes, was experimentally observed. The experimentally obtained group velocities versus frequency are consistent with numerical simulations. The principal longitudinal mode at low frequencies has been identified as the best candidate for damage detection on the grounding rods. The pulse-echo signals from the simulated corrosion pits are well correlated with the positions and cross-sectional areas of the pits. Wet-clay wrapping of the rods was used to simulate the influence of soil on the wave propagation. In the wet clay wrapped rods pulse-echo signals from the simulated corrosion pits are well correlated with the positions and cross-sectional areas of the pits, despite the significant attenuation of the echo signals. Acoustic pulse-echo methods based on acoustic guided waves have potential practical application for detecting corrosion-damage of the grounding rods.Graphical abstractGraphical abstract for this article
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