基于局部均值分解与快速独立成分分析的潜水泵故障诊断

doi:10.3969/j.issn.1000-1158.2020.05.13

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Abstract Aiming at the signal interference problem in fault diagnosis and analysis of submersible pumps, a method of combining local mean decomposition with independent component analysis was proposed. A series of product function components were obtained by decomposing the local mean value of the collected vibration signal, and the cross-correlation coefficient between each component and the vibration signal was calculated. The components with large cross-correlation number were selected to reconstruct and a matrix with the vibration signal was formed. The matrix was processed by fast independent component analysis, and the processed effective data was analyzed by spectrum analysis to get the final spectrum. Through specific experiments, the spectrum diagram of normal operation and fault operation after local mean decomposition and independent component analysis were compared, and the fault analysis and diagnosis were realized. Experimental results showed that the spectrum diagram processed by local mean decomposition and independent component analysis can clearly distinguish the fault characteristic frequency and improve the accuracy of fault diagnosis.

Key words： metrology fault diagnosis local mean decomposition fastICA algorithm signal processing submersible pump

Received: 29 October 2018 Published: 14 May 2020

PACS:	TB936
	TB973

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	TIAN Li-yong
	ZHANG Yi-zhe

Cite this article:

TIAN Li-yong,ZHANG Yi-zhe. Fault Diagnosis of Submersible Pumps Based on Local Mean Decomposition and Fast Independent Component Analysis[J]. Acta Metrologica Sinica, 2020, 41(5): 585-591.

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http://jlxb.china-csm.org:81/Jwk_jlxb/EN/10.3969/j.issn.1000-1158.2020.05.13 OR http://jlxb.china-csm.org:81/Jwk_jlxb/EN/Y2020/V41/I5/585

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