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Collaborative fault diagnosis decision fusion algorithm based on improved DS evidence theory

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

Abstract

DS evidence theory has in obtaining a correct diagnosis when confronted with highly conflicting evidence, a collaborative fault diagnosis decision fusion algorithm based on an improved version of DS evidence theory is proposed. The algorithm builds upon the closeness of certain kinds of evidence produced by existing DS evidence theory algorithms. According to the importance of the diagnostic information, weights are assigned to reduce the conflicting information while retaining the important diagnostic information. Simulated example shows that the algorithm could reduce the impact of conflicts in diagnostic information and improve the accuracy of the decision fusion process.

Publication Information

Output type

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

Original language

English

Pages from-to (Number of pages)

Pages 379-387

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

Chapter Number

47

External Publication IDs

  • Scopus: 85078476515

Host publication title

Advanced Manufacturing and Automation IX (IWAMA 2019)

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