Fault Feature Extraction Method of Gear Based on Improved Local Mean Decomposition and Instantaneous Energy Distribution-sample Entropy

doi:10.3901/JME.2016.05.169

Abstract

Abstract: A method of gear fault feature extraction based on an improved local mean decomposition (LMD) and instantaneous energy distribution (IED) - sample entropy (SampEn) is proposed. Aiming at end effects of LMD, the maximum similarity coefficient improved LMD method is put forward. The method achieves the improvement of end effect by looking for bands that have the biggest similarity coefficient to the specified bands at both ends in the internal signal. The simulation results show that this method can effectively improve the end effect of LMD. Using the improved LMD to decompose the signal can get instantaneous amplitude functions, from that, instantaneous energy distributions of the signal as sample entropy input of IED-SampEn can be obtained. Through the experimental study and compared with PF-SampEn, the results show that IED-SampEn can reasonably and effectively response gear fault state, it is typical as the feature vector of gear vibration signal and can be used as an effective fault feature.

Key words: fault feature extraction, gear, improved local mean decomposition, instantaneous energy distribution, sample entropy

CLC Number:

TN911

MENG Zong, WANG Yachao, HU Meng. Fault Feature Extraction Method of Gear Based on Improved Local Mean Decomposition and Instantaneous Energy Distribution-sample Entropy[J]. Journal of Mechanical Engineering, 2016, 52(5): 169-174.

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