湖南大学学报（自然科学版）Issue(10)：22-26,5.
基于EEMD 和改进VPMCD 的滚动轴承故障诊断方法
A Fault Diagnosis Method for Rolling Bearing Based on EEMD and Improved VPMCD
摘要
Abstract
Aiming at the defects of parameter estimation in VPMCD,BP neural network nonlinear re-gression method was used instead of the least squares method to solve the ill-conditioned problem that ex-ists in the least square method.Therefore,a fault diagnosis method for rolling bearing based on improved Variable Predictive Mode on the basis of Class Discriminate (VPMCD)was proposed.Firstly,Ensemble Empirical Mode Decomposition (EEMD)approach was used to decompose the rolling bearing vibration sig-nal into a number of single components;and then,the singular values were abstracted from the component matrix and formed feature vector which will act as an input in the improved VPMCD;finally,the work states and faults pattern of the rolling bearing can be identified.The analysis results from the experimental rolling bearing vibration signals have demonstrated that the proposed method can be effectively applied to the rolling bearing fault diagnosis.关键词
改进VPMCD/EEMD方法/奇异值分解/滚动轴承/故障诊断Key words
improved variable predictive mode based on class discriminate/ensemble empirical mode decomposition/singular value decomposition/rolling bearing/fault diagnosis分类
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程军圣,马利,潘海洋,杨宇..基于EEMD 和改进VPMCD 的滚动轴承故障诊断方法[J].湖南大学学报（自然科学版）,2014,(10):22-26,5.基金项目
国家自然科学基金资助项目(51175158,51075131) （51175158,51075131）
湖南省自然科学基金资助项目(11JJ2026) （11JJ2026）
