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10 October 2023 Transient extraction from doppler-shifted signal for track-side acoustic bearing fault diagnosis
Fang Liu, Yifan Xu, Taotao Zhai, Yongbin Liu
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Proceedings Volume 12799, Third International Conference on Advanced Algorithms and Signal Image Processing (AASIP 2023); 127992W (2023) https://doi.org/10.1117/12.3006054
Event: 3rd International Conference on Advanced Algorithms and Signal Image Processing (AASIP 2023), 2023, Kuala Lumpur, Malaysia
Abstract
One of the main reasons for train derailment is the failure of wheel bearings, and the track-side acoustic detection system (TADS) is one of the effective means to achieve online health monitoring. TADS is based on the basic principle that the acoustic signals emitted by the wheel bearings during the running of the train contain a wealth of diagnostic-related information. The challenge of this technology is how to accurately extract information reflecting the health condition of the wheel bearing from the sound signal. One of the main influence factors is the Doppler effect. To solve this problem, A new "Doppler Single Transient Model (DSTM)" and the "one-by-one stripping" strategy is developed to handle with the periodic fluctuation signal with Doppler distortion in this paper. It consists of three steps: (1) Use the Doppler Periodic Transient Model (DPTM) roughly estimate the parameters of the transient model; (2) The DSTM is used to extract transients from the signal one by one. (3) The optimization algorithms is used to accurately identify parameters. Through the proposed DSTM and the transient extraction strategy, the transients can be matched more accurately.
(2023) Published by SPIE. Downloading of the abstract is permitted for personal use only.
Citation Download Citation
Fang Liu, Yifan Xu, Taotao Zhai, and Yongbin Liu "Transient extraction from doppler-shifted signal for track-side acoustic bearing fault diagnosis", Proc. SPIE 12799, Third International Conference on Advanced Algorithms and Signal Image Processing (AASIP 2023), 127992W (10 October 2023); https://doi.org/10.1117/12.3006054
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KEYWORDS
Acoustics
Doppler effect
Wavelets
Bandpass filters
Signal detection
Signal processing
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