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An Enhanced Capacitive Angle Sensor Using Sine-Fitting Algorithm With Coherent Sampling

delete2025-01-01
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PRE
AI
P
Pei Huang
X
Xiaokang Liu
刘检华 (Jianhua Liu)
C
Changliang Wu
P
Peiyu Yu
B
Bingnan Zhan
DOI:10.1109/TIM.2025.3617400delete
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Abstract

Abstract

En 中文
Capacitive angle sensors cannot meet the current requirements of high-precision angle measurements due to their insufficient resolution. This study examines the dual-domain demodulation capability of current sine-fitting algorithms and proposes a modified sine-fitting algorithm with coherent sampling to enhance the resolution and noise-rejection capability of capacitive angle sensors. The proposed algorithm demodulates the angle using information obtained from both the amplitude and time domains, rather than relying on only one domain as in traditional methods. First, an advanced signal-processing circuit incorporating clock frequency allocation is developed to extract information from both the amplitude and time domains. This design ensures accurate demodulation using the sine-fitting algorithm. Second, the resolution and noise-rejection capability of different angle demodulation methods are analyzed in detail, and the mechanism by which dual-domain demodulation contributes to improving the resolution is elucidated. Finally, the experimental results show that the proposed sine-fitting algorithm can improve the noise-rejection capability of a capacitive angle sensor by a factor of 14, and the resolution can reach $0.0036"$ . This exceptional resolution enables the application of a capacitive angle sensor in high-precision angle measurement.
Keywords:
Clock frequency allocation
coherent sampling
high-resolution angle sensor
noise-rejection
sine-fitting algorithm

Journal

IEEE Transactions on Instrumentation and Measurement cover
IEEE Transactions on Instrumentation and Measurement
IF:
5.9
Papers:
1.9W
Citations:
5.8W

Organization

B
beijing institute of technology
Scholars:
5.4W
Papers: 4.0W
Citations: 63
C
Chongqing University of Technology
Scholars:
5.8K
Papers: 3.5K
Citations: 3