Paper Title:
Multivariate Statistical Process Monitoring and Fault Diagnosis Based on an Integration Method of PCA-ICA and CSM
  Abstract

In this paper, an approach for multivariate statistical process monitoring ans fault diagnosis based on an improved independent component analysis (ICA) and continuous string matching (CSM) is presented, which can detect and diagnose process fault faster and with higher confidence level. The trial on the Tennessee Eastman process demonstrates that the proposed method can diagnose the fault effectively. Comparison of the method with the well established principal component analysis is also made.

  Info
Periodical
Chapter
Control, Constitutive Modeling and Simulation
Edited by
Aimin Yang, Jingguo Qu and Xilong Qu
Pages
110-114
DOI
10.4028/www.scientific.net/AMM.84-85.110
Citation
Y. H. Yang, Y. L. Chen, X. B. Chen, S. K. Qin, "Multivariate Statistical Process Monitoring and Fault Diagnosis Based on an Integration Method of PCA-ICA and CSM", Applied Mechanics and Materials, Vols. 84-85, pp. 110-114, 2011
Online since
August 2011
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Price
$32.00
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