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Research on Signal Noise Reduction Methods for Force Sensors
ID：90 View Protection：ATTENDEE Updated Time：2025-10-11 22:50:25 Hits：235 Poster Presentation

Start Time：2025-11-09 09:06（Asia/Shanghai）

Duration：1min

Session：P Poster presentation » P55.Wireless power transfer technology

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Abstract
To address issues such as low signal-to-noise ratio and complex noise types in static measurements of force sensors, this paper proposes a noise reduction method based on
the fusion of two-layer wavelet decomposition and LMS adaptive filtering. This method first employs median filtering to eliminate isolated impulse noise as preprocessing. Subsequently, it utilizes Daubechies4 (db4) and Symlets8 (sym8) wavelet bases for two-stage cascaded wavelet decomposition and thresholding, effectively suppressing multi-frequency noise. Following this, an LMS adaptive filter intelligently suppresses residual noise. Experimental results demonstrate that this method outperforms
traditional single-wavelet denoising approaches in terms of signal-to-noise ratio (SNR) and root mean square error (RMSE). It achieves significant noise reduction while preserving signal morphological features, indicating its feasibility for processing force sensing signals.
Keywords
Adaptive filtering;Force sensor signal;LMS algorithm; Signal denoising;Wavelet decomposition
Speaker
qing li
Student Anhui Jianzhu University

Submission Author
qing li Anhui Jianzhu University
Huibin Cao Hefei Institutes of Physical Science Chinese Academy of Sciences
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Important Date

  • Conference Date

    Nov 07

    2025

    to

    Nov 09

    2025

  • Oct 30 2025

    Draft paper submission deadline

  • Nov 10 2025

    Registration deadline

Sponsored By
IEEE西南交通大学IAS学生分会
Organized By
西南交通大学电气工程学院
SPACI车网关系研究室
四川大学电力系统稳定与高压直流输电研究团队
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