Weighted Basis Pursuit Denoising Algorithm and Its Application in Gear Fault Diagnosis

In order to improve the fault signature extracting performance in signal processing for gearboxes' fault diagnosis, a weighted Basis Pursuit Denoising(BPD) algorithm is proposed. The algorithm introduces weighted matrix into classical BPD model which picks small threshold values for target freq...

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Bibliographic Details
Published in2021 International Conference on Sensing, Measurement & Data Analytics in the era of Artificial Intelligence (ICSMD) pp. 1 - 5
Main Authors Zhou, Jianghan, Wang, Shibin, Tong, Chaowei, Zhao, Zhibin, Chen, Xuefeng
Format Conference Proceeding
LanguageEnglish
Published IEEE 21.10.2021
Subjects
Data analysis
Fault diagnosis
gear fault diagnosis
Gears
Interference
ISTA
Noise reduction
Performance evaluation
signal processing
Signal processing algorithms
sparse representation
weighted Basis Pursuit Denoising
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Summary:In order to improve the fault signature extracting performance in signal processing for gearboxes' fault diagnosis, a weighted Basis Pursuit Denoising(BPD) algorithm is proposed. The algorithm introduces weighted matrix into classical BPD model which picks small threshold values for target frequencies letting them stand out in the spectrum after iteration. The algorithm is verified by both simulation signal and an actual gear fault signal from a test bench, in which the algorithm shows great performance and excellent capability of extracting signal feature of gear fault under complex interference and strong noises distraction.
DOI:10.1109/ICSMD53520.2021.9670855