Hydraulic pump fault diagnosis method based on SGMD-autogram

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Journal of Vibration and Shock ›› 2020, Vol. 39 ›› Issue (23) : 234-241.

ZHENG Zhi1, 2, LI Xianze1, ZHU Yong3, WANG Baozhong1

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Abstract

The symplectic geometry mode decomposition (SGMD) method has the problem of feature information distribution being too scattered, and Autogram method has the problem of the feature extraction ablility of the maximal overlap discrete wavelet packet transform (MODWPT) being not strong.Here, aiming at above problems, a new method based on SGMD and Autogram was proposed.Firstly, SGMD was applied to decompose measured multi-mode vibration fault signals of hydraulic pump.Secondly, aiming at the problem of too scattered feature information distribution after decomposition, the spectral kurtosis method based on maximum unbiased autocorrelation was proposed.Some mode components containing rich operating feature information were screened out as the data source to replace MODWPT, and realize the extraction of the optimal fault features.Finally, the data source was processed with threshold, and the fault diagnosis of hydraulic pump was realized based on spectrum.By comparing and analyzing simulated and measured vibration fault signals of hydraulic pump swash plate, it was verified that the proposed method can effectively diagnose hydraulic pump swash plate faults.

Key words

hydraulic pump / fault diagnosis / symplectic geometry mode decomposition (SGMD) / Autogram

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ZHENG Zhi1, 2, LI Xianze1, ZHU Yong3, WANG Baozhong1. Hydraulic pump fault diagnosis method based on SGMD-autogram[J]. Journal of Vibration and Shock, 2020, 39(23): 234-241

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