燕山大学学报2016，Vol.40Issue(6)：493-498,6.DOI:10.3969/j.issn.1007-791X.2016.06.004
基于HHT边际谱熵-马氏距离的滚动轴承故障诊断
Fault diagnosis of rolling bearing based on HHT marginal spectrum entropy-Mahalanobis distance
摘要
Abstract
In the light of the non⁃stationary characteristics of the rolling bearing vibrating signals a new fault diagnosis method is proposed for the rolling bearing based on HHT marginal spectrum entropy and Mahalanobis distance according to the Hilbert Huang transform theory and the concept of generalized information entropy.First the known normal signals and fault signals measured in the same load but with different faults are pretreated based on the effective wavelet threshold de⁃noising. Second the EMD Hilbert spectrum and Hilbert marginal spectrum are analyzed by utilizing Hilbert⁃Huang transform technique and the marginal spectrum energy entropy function is defined according to the concept of generalized information entropy. Finally the Mahalanobis distance is used to classify the working state and fault type of the rolling bearing based on the feature function. The results show that the fault diagnosis of rolling bearing can be realized accurately and effectively by utilizing the proposed method. The proposed method can provide a good reference for the actual rolling bearing fault diagnosis.关键词
HHT/边际谱熵/马氏距离/故障诊断Key words
HHT marginal spectrum entropy/Mahalanobis distance/fault diagnosis分类
机械制造引用本文复制引用
李巧艺,单奇,陈跃威..基于HHT边际谱熵-马氏距离的滚动轴承故障诊断[J].燕山大学学报,2016,40(6):493-498,6.基金项目
国家自然科学基金资助项目 （）
