Fault diagnosis of rolling bearing of wind turbine generator based on PSO-SEBD

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Journal of Vibration and Shock ›› 2023, Vol. 42 ›› Issue (7) : 281-288.

WANG Pengcheng1,2, DENG Aidong1,2, LING Feng1,2, DENG Minqiang1,2, LIU Yang1,2

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Abstract

As a key component of the transmission system of a wind turbine, the rolling bearing is vital to the safe and stable operation of the entire unit. Aiming at the problem of rolling bearing fault diagnosis, On base of extracting cyclo-stationarity of repetitive transients from envelope spectrum based on prior-unknown blind deconvolution technique, a SEBD bearing fault diagnosis method based on particle swarm optimization (PSO) optimization is proposed to realize the adaptive selection of SEBD filter length. Firstly, take the maximum fault characteristic frequency ratio (CFR) as the fitness function, and use the PSO algorithm to optimize the filter length; then, use the obtained optimal filter length to perform SEBD processing; finally, according to the envelope spectrum feature of the signal after SEBD processing realizes the effective identification of bearing faults. The effectiveness of PSO-SEBD is verified by analyzing the simulation signal and the public bearing failure data of Paderborn University in Germany. By comparing with several commonly used diagnostic methods and analyzing under noisy environment, it shows that this method has better diagnostic performance and anti-noise ability.

Key words

Rolling bearing / Fault diagnosis / Blind deconvolution technique / Particle swarm optimization

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WANG Pengcheng1,2, DENG Aidong1,2, LING Feng1,2, DENG Minqiang1,2, LIU Yang1,2. Fault diagnosis of rolling bearing of wind turbine generator based on PSO-SEBD[J]. Journal of Vibration and Shock, 2023, 42(7): 281-288

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