Multi-space PCA with its Application in Fault Diagnosis

摘要：

　　Traditional PCA method can detect big failures with obvious signs of abnormality effectively.But it does not seem to apply for failures with smaller signs drowned in the noise or big failures.Meanwhile,there is still not a clear and consistent explanation for the impact of the PCA subspace decomposition on the fault detection capability.In this paper,aiming at fault diagnosis with small signs,a method of multi-space principal component analysis is proposed based on the research on the effect of subspace decomposition on the capability of fault diagnosis,which is applied into the process monitoring.Case studies validate the effectiveness of the proposed approaches.

关键词： PCA,Fault Diagnosis Characteristic Transformation Matrix Diagnosis Subspaces

作者: HU Jing WEN Chenglin LI Ping WANG Chunxia

作者单位: Department of Control Science and Control Engineering,Zhejiang University,Hangzhou 310027,China School of Automation,Hangzhou Dianzi University,Hangzhou 310018,China

会议类型: 国际会议

会议名称: The 33th Chinese Control Conference第33届中国控制会议

会议地点: 南京

会议语种:英文

页码: 3311-3316

在线出版日期: 2014-07-28（万方平台首次上网日期，不代表论文的发表时间）