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Weighted assignment fusion algorithm of evidence conflict based on Euclidean distance and weighting strategy, and application in the wind turbine system

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  • Liming Gou
  • Jian Zhang
  • Naiwen Li
  • Zongshui Wang
  • Jindong Chen
  • Lin Qi

Abstract

In the process of intelligent system operation fault diagnosis and decision making, the multi-source, heterogeneous, complex, and fuzzy characteristics of information make the conflict, uncertainty, and validity problems appear in the process of information fusion, which has not been solved. In this study, we analyze the credibility and variation of conflict among evidence from the perspective of conflict credibility weight and propose an improved model of multi-source information fusion based on Dempster-Shafer theory (DST). From the perspectives of the weighting strategy and Euclidean distance strategy, we process the basic probability assignment (BPA) of evidence and assign the credible weight of conflict between evidence to achieve the extraction of credible conflicts and the adoption of credible conflicts in the process of evidence fusion. The improved algorithm weakens the problem of uncertainty and ambiguity caused by conflicts in the information fusion process, and reduces the impact of information complexity on analysis results. And it carries a practical application out with the fault diagnosis of wind turbine system to analyze the operation status of wind turbines in a wind farm to verify the effectiveness of the proposed algorithm. The result shows that under the conditions of improved distance metric evidence discrepancy and credible conflict quantification, the algorithm better shows the conflict and correlation among the evidence. It improves the accuracy of system operation reliability analysis, improves the utilization rate of wind energy resources, and has practical implication value.

Suggested Citation

  • Liming Gou & Jian Zhang & Naiwen Li & Zongshui Wang & Jindong Chen & Lin Qi, 2022. "Weighted assignment fusion algorithm of evidence conflict based on Euclidean distance and weighting strategy, and application in the wind turbine system," PLOS ONE, Public Library of Science, vol. 17(1), pages 1-20, January.
    • Handle: RePEc:plo:pone00:0262883
    DOI: 10.1371/journal.pone.0262883
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    References listed on IDEAS

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    1. Wen Jiang & Shiyu Wang & Xiang Liu & Hanqing Zheng & Boya Wei, 2017. "Evidence conflict measure based on OWA operator in open world," PLOS ONE, Public Library of Science, vol. 12(5), pages 1-18, May.
    2. Atiye Sarabi-Jamab & Babak N Araabi, 2020. "An information-based approach to handle various types of uncertainty in fuzzy bodies of evidence," PLOS ONE, Public Library of Science, vol. 15(1), pages 1-13, January.
    3. Marzieh Mokarram & Hamid Reza Pourghasemi & John P. Tiefenbacher, 2020. "Using Dempster–Shafer theory to model earthquake events," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 103(2), pages 1943-1959, September.
    4. Tian, Qun & Huang, Gang & Hu, Kaiming & Niyogi, Dev, 2019. "Observed and global climate model based changes in wind power potential over the Northern Hemisphere during 1979–2016," Energy, Elsevier, vol. 167(C), pages 1224-1235.
    5. Tangfan Xiahou & Yu Liu, 2020. "Reliability bounds for multi-state systems by fusing multiple sources of imprecise information," IISE Transactions, Taylor & Francis Journals, vol. 52(9), pages 1014-1031, September.
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