A New Gear Fault Identification Method Based on EEMD Permutation Entropy and Grey Relation Degree

被引：0

作者：

Zhang, Wenbin ^{[1
]}

Tan, Yushuo ^{[2
]}

Pu, Yasong ^{[1
]}

机构：

[1] Honghe Univ, Coll Engn, Mengzi 661199, Yunnan, Peoples R China

[2] Shijiazhuang Posts & Telecommun Tech Coll, Shijiazhuang 050021, Hebei, Peoples R China

来源：

2020 13TH INTERNATIONAL CONGRESS ON IMAGE AND SIGNAL PROCESSING, BIOMEDICAL ENGINEERING AND INFORMATICS (CISP-BMEI 2020) | 2020年

基金：

中国国家自然科学基金;

关键词：

permutation entropy; grey relation degree; fault identification; EEMD; gear;

D O I：

暂无

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

In this paper, a new fault identification method was proposed based on EEMD permutation entropy and grey relation degree. Firstly, the sampled data was denoised by morphological filter. Secondly, the denoised signal was decomposed into a finite number of stationary intrinsic mode functions (IMF). Thirdly, the permutation entropy were calculated to express some containing the most dominant fault information. Different fault type corresponds with different permutation entropy distribution. Finally, the grey relation degree between the symptom set and standard fault set was calculated as the identification evidence for fault diagnosis. The practical results show that this method is quite effective in gear fault identification. It's suitable for on-line monitoring and diagnosis of gear system.

引用

页码：542 / 547

页数：6

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