Translated Titles

Application of Improved PCA to Fermentation Process Monitoring and Fault Diagnosis


肖应旺(Ying-Wang Xiao);徐保国(Bao-Guo Xu)

Key Words

主元分析 ; 统计过程监测 ; 发酵 ; 故障诊断 ; PCA ; statistical process monitoring ; fermentation ; fault diagnosis



Volume or Term/Year and Month of Publication

20卷5期(2005 / 05 / 01)

Page #

571 - 574

Content Language


Chinese Abstract


English Abstract

An improved principal component analysis (PCA) is presented which uses principal-component-related variable residual (PVR) statistic to replace Q-statistic. The principal components in PCA is decided by virtue of cumulative percent variance and multi-correlation coefficients. The improved PCA is applied to mycetozoan fermentation process monitoring and fault diagnosis. The simulation result shows that the improved PCA can avoid the conservation of Q-statistical test and ensure enough information in principal component subspace. Compared with a system performance monitoring based on characteristic subspace, the improved PCA is more effective.

Topic Category 基礎與應用科學 > 資訊科學
工程學 > 機械工程
工程學 > 電機工程