Abstract
This research investigates real time tilting measurement using Micro-Electro-Mechanical-system (MEMS) based inertial measurement unit (IMU). Accelerometers suffer from errors caused by external accelerations that sums to gravity and make accelerometers based tilting sensing unreliable and inaccurate. Gyroscopes can offset such drawbacks but have data drifting problems. This paper presents a study on complementary and Kalman filter for tilting measurement using MEMS based IMU. The complementary filter algorithm uses low-pass filter and high-pass filter to deal with the data from accelerometer and gyroscope while Kalman filter takes the tilting angle and gyroscope bias as system states, combining the angle derived from the accelerometer to estimate the tilting angle. The study carried out both static and dynamic experiments. The results showed that both Complementary and Kalman filter were less sensitive to variations and almost no signal coupling phenomenon and able to obtain smooth and accurate results.
Original language | English |
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Title of host publication | Proceedings of the 2015 10th IEEE Conference on Industrial Electronics and Applications (ICIEA 2015) |
Place of Publication | Piscataway, NJ |
Publisher | Institute of Electrical and Electronics Engineers (IEEE) |
Pages | 2004-2009 |
Number of pages | 6 |
ISBN (Electronic) | 9781467373173, 9781479983896 |
ISBN (Print) | 9781479984671 |
DOIs | |
Publication status | Published - 2015 |
Externally published | Yes |
Event | 10th IEEE Conference on Industrial Electronics and Applications, ICIEA 2015 - Auckland, New Zealand Duration: 15 Jun 2015 → 17 Jun 2015 |
Other
Other | 10th IEEE Conference on Industrial Electronics and Applications, ICIEA 2015 |
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Country/Territory | New Zealand |
City | Auckland |
Period | 15/06/15 → 17/06/15 |
Keywords
- complementary filter
- IMU
- tilt measurement
- Kalman filter
- data fusion