重庆大学学报2017，Vol.40Issue(7)：25-31,7.DOI:10.11835/j.issn.1000-582X.2017.07.004
单通道旋转机械复合故障信号分离及诊断
Blind source separation and fault diagnosis of Single-channel rotating mechanical compound fault signal
摘要
Abstract
To solve the problem that the separation and the fault diagnosis of rotating mechanical compound fault signal always difficult to obtain desired results under the condition of single-channel,first,the method of ensemble empirical mode decomposition (EEMD) was applied to build the virtual channels and the method of linear local tangent space alignment (LLTSA) was applied to reduce the dimension,which solved the problem of underdetermined blind source separation well.Then,training the over-complete dictionary and using the method of signal sparse decomposition to extract the sparse characteristics of rotating mechanical compound fault signal.Finally,the support vector machine was employed to evaluate the effect of signal separation and fault diagnosis method.Moreover,the proposed method was applied to the experiment of rolling bearing fault diagnosis,and it's found that the separation and classification of compound fault signal was completed efficiently.关键词
盲源分离/稀疏表示/特征提取/故障诊断Key words
blind source separation/sparse representation/feature extraction/fault diagnosis分类
机械制造引用本文复制引用
刘嘉敏,刘军委,彭玲..单通道旋转机械复合故障信号分离及诊断[J].重庆大学学报,2017,40(7):25-31,7.基金项目
中央高校基本科研业务费资助项目(1061120131207,12120001) （1061120131207,12120001）
重庆市研究生科研创新项目(CYS14028).Supported by the Fundamental Research Funds for the Central Universities(1061120131207,12120001) and the Innovation Fund Designated for Graduate Students of Chongqing(CYS14028). （CYS14028）
