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American Journal of Sensor Technology
Number of Followers: 4

This is an Open Access Journal

Open Access journal
ISSN (Print) 2373-3454 - ISSN (Online) 2373-3462
Published by Science and Education Publishing

[75 journals]

Angular Position Estimation of an Inverted Pendulum Using Low-Cost IMUs
- Authors: Daisuke Aoyagi; Sukgi Choi
  Pages: 1 - 6
  Abstract: Seeking an affordable solution to measure a bicycle’s roll angle, we came across an Inertial Measurement Unit (IMU) BNO055 by Bosch, which contains 3-axis accelerometer, gyroscope, and magnetometer, and is advertised to produce “absolute orientation” by a built-in proprietary “Fusion” algorithm. We found another low-cost IMU, an MPU-9250 from InvenSense, which could also calculate absolute orientation via embedded Fusion software. Being unable to find information about dynamic characteristics of these IMUs in their datasheets, we sought to evaluate them under dynamic conditions, specifically in the estimation of roll angle. We constructed an inverted pendulum as a model of a bicycle, mounted both IMUs on it, and attached a potentiometer to measure actual angular position for reference. Additionally, as an alternative to the proprietary Fusion algorithms, we devised and implemented an Extended Kalman Filter, which, we hypothesized, would perform better than the proprietary Fusion algorithms, because our algorithm incorporated the kinematics of the inverted pendulum while the Fusion algorithm of the IMUs did not. In a series of experiments, we observed a significant time lag, about 0.05-0.1 second, in BNO055’s raw acceleration and gyro signals. The BNO055’s Fusion responded with similar lag and an offset of 0.5-3°; we also noticed rather unpredictable fluctuation in the output signals, possibly due to its “automatic calibration” feature, which cannot be disabled. The MPU-9250 exhibited better performance than the BNO055 in terms of raw acceleration signals and, particularly, gyro signals. The MPU-9250’s Fusion performed somewhat better than BNO055’s, typically showing lag of 0.03-0.06 sec and static offset of 0.5-1°. Our implementation of Kalman Filter based on MPU-9250 raw signal performed better than either Fusion algorithm, with about 0.02-0.03 second lag and 0.5-1° offset, supporting our hypothesis. Our next step is to experiment on an actual bicycle in motion.
  PubDate: 2018-09-09
  DOI: 10.12691/ajst-5-1-1
  Issue No: Vol. 5, No. 1 (2018)
Single-chip Implementation of LVDT Signal Conditioning
- Authors: Lars E. Bengtsson
  Pages: 7 - 16
  Abstract: The aim of this work was to prove that the signal conditioning electronics for linear variable transformers (LVDTs) can be implemented in inexpensive, general-purpose 8-bit microcontrollers, making expensive dedicated signal conditioning chips redundant. A low-cost, high-resolution signal conditioning solution for LVDTs is presented. Apart from a few external passive components, the entire solution is implemented in a low-cost, analog-digital hybrid microcontroller. The excitation sinusoid is generated by filtering out the fundamental frequency of a (self-sustained) pwm-generated square wave and the secondary coils’ signals are demodulated with classic peak detector circuits implemented in the microcontroller using a combination of its embedded analog and digital building blocks. A resolution of 1 μm over a range of ±6.35 mm for a commercial LVDT is reported and an uncertainty of 6 μm in the absolute value is deduced. The entire solution is implemented as surface mounted components on a small printed circuit board and the LVDT core displacement is displayed on an LCD display. Due to the simplicity and low-cost components required, this signal conditioning proposal has the potential to have a significant impact on commercial LVDT signal conditioning chips in the future since it is significantly less expensive than the present state-of-the-art signal conditioning chips offered by the main commercial suppliers and other solutions previously suggested in scientific literature.
  PubDate: 2018-12-14
  DOI: 10.12691/ajst-5-1-2
  Issue No: Vol. 5, No. 1 (2018)

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