ANSMD方法及其在齿轮故障诊断中的应用

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Abstract Aiming at the difficulty of effectively processing signals with non-stationary and nonlinear characteristics by traditional signal analysis methods, an adaptive nonlinear sparse mode decomposition (ANSMD) is proposed. ANSMD method can adaptively decompose a complex signal into several local narrow-band components with physical meaning of instantaneous frequency by constraining the singular local linear operator into signal decomposition, and local narrow-band components are iterated as basic functions. Therefore, the original signal is approached to realize the adaptive decomposition of the signal, and then the complete time-frequency distribution of the original signal is obtained. Experimental verification through simulation signals and gear crack fault signals shows that, compared with EMD, LCD and VMD methods, the ANSMD method has superior performance in suppressing modal aliasing and robustness, and can effectively diagnose gear faults.

Key words： Signal processing Gear Fault diagnosis Adaptive nonlinear sparse mode decomposition;

Received: 22 June 2020 Published: 15 November 2021

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	Articles by authors
	PAN Haiyang1
	2
	JIANG Wanwan2
	ZHENG Jinde1
	2
	PAN Ziwei2

Cite this article:

PAN Haiyang1,2,JIANG Wanwan2, et al. ANSMD method and its application in gear fault diagnosis[J]. JOURNAL OF VIBRATION AND SHOCK, 2021, 40(21): 113-119.

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http://jvs.sjtu.edu.cn/EN/ OR http://jvs.sjtu.edu.cn/EN/Y2021/V40/I21/113

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