Gear Fault Feature Extraction Based on Full Vector Permutation Entropy

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Journal of Vibration and Shock ›› 2016, Vol. 35 ›› Issue (11) : 224-228.

Hao Wangshen, Wang Hongmin,Dong Xinmin, Hao Wei, Han Jie, Zhang Kun

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Abstract

Gear fault vibration signals are often non-stationary and non-linear, and permutation entropy can well reflect the degree of disorder of a one-dimensional time series and the dynamics of the mutant signal. However, the traditional fault diagnosis method based on a single source of vibration signal can’t ensure the integrity of the information. This article will apply permutation entropy algorithm to the two-channel homologous signal, presenting a method of gear fault feature extraction based on full vector permutation entropy. Experimental results show that this method can effectively reflect the mutation of signals, avoid misdiagnosis caused by a single channel information which is imperfect.

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non-linear / permutation entropy / full vector permutation entropy / fault feature / gear

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Hao Wangshen, Wang Hongmin,Dong Xinmin, Hao Wei, Han Jie, Zhang Kun. Gear Fault Feature Extraction Based on Full Vector Permutation Entropy[J]. Journal of Vibration and Shock, 2016, 35(11): 224-228

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