Fault Diagnosis of Rolling Element Bearing Using Multi-Scale Lempel-Ziv Complexity and Mahalanobis Distance Criterion

被引：9

作者：

Yu K. ^{[1
]}

Tan J. ^{[1
]}

Lin T. ^{[1
]}

机构：

[1] School of Mechanical and Automotive Engineering, Qingdao University of Technology, Shandong, 266525, Qingdao

来源：

Journal of Shanghai Jiaotong University (Science) | 2018年 / 23卷 / 5期

基金：

中国国家自然科学基金; 高等学校博士学科点专项科研基金;

关键词：

fault diagnosis; Lempel-Ziv complexity (LZC); Mahalanobis distance (MD) criterion; rolling element bearing; TH; 165.3;

D O I：

10.1007/s12204-018-1965-2

中图分类号：

学科分类号：

摘要：

A new fault diagnosis technique for rolling element bearing using multi-scale Lempel-Ziv complexity (LZC) and Mahalanobis distance (MD) criterion is proposed in this study. A multi-scale coarse-graining process is used to extract fault features for various bearing fault conditions to overcome the limitation of the single stage coarse-graining process in the LZC algorithm. This is followed by the application of MD criterion to calculate the accuracy rate of LZC at different scales, and the best scale corresponding to the maximum accuracy rate is identified for fault pattern recognition. A comparison analysis with Euclidean distance (ED) criterion is also presented to verify the superiority of the proposed method. The result confirms that the fault diagnosis technique using a multi-scale LZC and MD criterion is more effective in distinguishing various fault conditions of rolling element bearings. © 2018, Shanghai Jiaotong University and Springer-Verlag GmbH Germany, part of Springer Nature.

引用

页码：696 / 701

页数：5

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