FAULT DETECTION BEHAVIOR ANALYSIS OF PCA-BASED PROCESS MONITORING APPROACH

WANG Haiqing; SONG Zhihuan; WANG Hui

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FAULT DETECTION BEHAVIOR ANALYSIS OF PCA-BASED PROCESS MONITORING APPROACH

更新时间：2025-12-10

- FAULT DETECTION BEHAVIOR ANALYSIS OF PCA-BASED PROCESS MONITORING APPROACH
- CIESC Journal Issue 3, (2002)
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- Online First：25 March 2002，
  
  Published：25 March 2002
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WANG Haiqing, SONG Zhihuan, WANG Hui. FAULT DETECTION BEHAVIOR ANALYSIS OF PCA-BASED PROCESS MONITORING APPROACH[J]. CIESC Journal, 2002, (3).
DOI：

WANG Haiqing, SONG Zhihuan, WANG Hui. FAULT DETECTION BEHAVIOR ANALYSIS OF PCA-BASED PROCESS MONITORING APPROACH[J]. CIESC Journal, 2002, (3). DOI：

摘要

通过分别导出T2 和SPE统计量均值与过程数据统计参数之间的关系

分析了影响主元分析 (PCA)检测行为的因素以及工况变化与故障在PCA下的不同被检测行为

利用双效蒸发过程的仿真监测验证了获得的结果

指出了通常关于PCA检测行为的一些不准确的结论

Abstract

Principal component analysis (PCA) is an effective approach to process monitoring and quality control.Although extensive researches related with PCA-based process monitoring approaches have been reported

the characteristics and fault detecting behavior of PCA are still equivocal.The commonly accepted conclusions in this field often conflict with the root cause of process malfunction and lead to incorrect understanding of the detection results.The expectations of T 2 and SPE statistics are studied in this paper and their relations to the statistical parameters of process data are presented.These relationships reveal the influence factors of the T 2 and SPE tests and give a definite description of the detection behavior of PCA.Based on these relationships process disturbances and faults can be distinguished

which make further fault diagnosis more reliable.The acquired results are illustrated and verified by monitoring of a simulated double-effective evaporator.

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