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A new fault identification method based on combined reconstruction contribution plot and structured residual

  • Bo Chen
    ,
  • Kesheng Wang
    ,
  • Xiue Gao
    ,
  • ,
  • Shifeng Chen
    ,
  • Tianshu Zhang
Research Output: Chapter in Book/Report/Conference proceeding Chapter Peer-review

Abstract

The existing contribution plot-based reconstruction fault identification methods suffer from low identification accuracy and serious trailing effect. In this paper, a new fault identification method is proposed based on a combination of reconstruction contribution plot and structured residual method. The fault direction vector is calculated by utilizing the structured residual method. The reconstruction contribution plot utilizes the obtained fault direction vector to accurately localize the fault variable, where the fault source can be accurately localized subsequently. The experimental results show that, compared with the traditional PCA and PPCA (PCA based on probability) reconstruction contribution method, this algorithm can accurately identify the fault variables, and reduce the influence of the fault variables on the non-fault variables.

Publication Information

Output type

Research Output: Chapter in Book/Report/Conference proceeding Chapter Peer-review

Host publication Subtitle

Conference proceedings

Original language

English

Article number

Chapter 35

Pages from-to (Number of pages)

Pages 283-291

Publication milestones

  • Published - 03/01/2020

Publication status

Published - 03/01/2020

Publisher

Springer, Japan, India, Australia, Germany, United States, United Arab Emirates, Austria, Switzerland, Italy, China, United Kingdom, Netherlands, Brazil, France, Singapore

Publication series

  • Publication series name: Advanced Manufacturing and Automation IX
    ISSN (Print): 1876-1100
    ISSN (Electronic): 1876-1119
    Volume: 634
9789811523403, 9789811523434

ISBN (Electronic)

9789811523410

External Publication IDs

  • Scopus: 85078411509

Host publication title

Advanced Manufacturing and Automation IX

Host publication editors

  • Yi Wang
  • Kristian Martinsen
  • Tao Yu
  • Kesheng Wang

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