中国机械工程Issue(11)：1492-1497,6.DOI:10.3969/j.issn.1004-132X.2014.11.013
基于OC-VPMCD和ITD的滚动轴承故障诊断方法
Rolling Bearing Fault Diagnosis Method Based on OC-VPMCD and ITD
摘要
Abstract
Variable predictive model based class discriminate (VPMCD)is a way to pattern recog-nitions.It made full use of the inner relations among characteristic values extracted from those origi-nal data to recognize models and classified the faults by minimum prediction error sum of squares val-ue.Based on that,the paper proposed a new one-class classification method-OC-VPMCD and com-bined OC-VPMCD with ITD and applied into the rolling bear fault diagnosis.Firstly,rolling bearing vibration signals would be adaptively decomposed by ITD and the permutation entropy of proper rota-tions (PR)which contain the main fault information would be extracted as characteristic values.Sec-ondly,OC-VPMCD classifier would be trained and determined the prediction error sum of squares threshold value.Finally,the OC-VPMCD classifier would be used to complete pattern recognitions;according to the pattern recognitions results the working states of the rolling bearing were j udged. The experimental results show that this method can be applied to rolling bearing fault diagnosis effec-tively.关键词
单类基于变量预测模型的模式识别/本征时间尺度分解/排列熵/滚动轴承/故障诊断Key words
one-class variable predictive model based class discriminate(OC-VPMCD)/intrinsic time-scale decomposition(ITD)/permutation entropy/rolling bearing/fault diagnosis分类
机械制造引用本文复制引用
程军圣,马兴伟,李学军,杨宇..基于OC-VPMCD和ITD的滚动轴承故障诊断方法[J].中国机械工程,2014,(11):1492-1497,6.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）
湖南省机械设备健康维护重点实验室开放基金资助项目(201202) （201202）
