基于连续交叉小波相干分析和自适应CYCBD的轴承故障诊断

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Abstract Maximum second-order cyclostationarity blind deconvolution method (CYCBD), an effective method for bearing fault diagnosis, can recover periodic impulse from strong background noise signals. The fault characteristic frequency is the key parameter of CYCBD, but there are deviations of fault characteristic frequency between the real value and the theoretical value because of manufacturing errors and roller slippage in rolling bearings that reduces the effectiveness of CYCBD. Meanwhile, the test signal of the fault bearing contains a large amount of noise and harmonic interference, which also reduces the fault feature extraction capability of CYCBD. In this regard, a bearing fault diagnosis method based on continuous cross wavelet coherence analysis and adaptive CYCBD was proposed. Firstly, the bearing fault resonance band is obtained using cross-wavelet coherence analysis of the test signals from normal and faulty bearings. Secondly, a new period detection technique based on three normalized period detection indicators is proposed to obtain accurate bearing fault characteristic frequencies. Finally, based on the bearing fault resonance band signal and the real bearing fault characteristic frequency, CYCBD filtering is performed, and Teager energy operator demodulation analysis is performed for the filtered signal to obtain the energy spectrum for bearing fault diagnosis. The analysis results of the simulation signals and the test signals of traction motor bearings in high-speed trains demonstrate that the method can effectively detect the bearing fault and is outperforming the traditional CYCBD method.

Key words： maximum second-order cyclostationarity blind deconvolution continuous cross wavelet coherence analysis fault period detection techniques for bearings traction motor bearings in high-speed trains fault diagnosis

Received: 06 October 2022 Published: 15 November 2023

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	Articles by authors
	YANG Gang1
	QIN Limu1
	L Kun1
	LI Hengkui2

Cite this article:

YANG Gang1,QIN Limu1,L Kun1, et al. Bearing fault diagnosis based on continuous cross wavelet coherence analysis and adaptive CYCBD[J]. JOURNAL OF VIBRATION AND SHOCK, 2023, 42(21): 17-28.

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http://jvs.sjtu.edu.cn/EN/ OR http://jvs.sjtu.edu.cn/EN/Y2023/V42/I21/17

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