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An Intelligent Fault Analysis and Diagnosis System for Electromagnet Manufacturing Process Based on Fuzzy Fault Tree and Evidence Theory

Author

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  • Jihong Pang

    (College of Business, Shaoxing University, Shaoxing 312000, China)

  • Jinkun Dai

    (College of Mechanical and Electrical Engineering, Wenzhou University, Wenzhou 325035, China)

  • Yong Li

    (College of Mechanical and Electrical Engineering, Wenzhou University, Wenzhou 325035, China)

Abstract

Because an electromagnet has a complex structure and manufacturing process, it is difficult to analyze the overall failure of the electromagnet. In order to solve this problem, a fault intelligent analysis and diagnosis system based on fuzzy fault tree and evidence theory is proposed in this paper. First, the failure structure and fuzzy fault tree are generated according to the experience. Second, the probability of failure caused by basic events is obtained based on the data statistics of the insufficient holding force of the electromagnet in the past. Then, the probability of the basic events is given by using the synthesis rules of evidence theory. Next, the belief interval of the basic event is set as the fuzzy number, and the intelligent analysis is completed by using the calculated fuzzy importance. Finally, the validity and feasibility of the proposed method is proved by using the failure of insufficient retention force in the electromagnet manufacturing process as an example.

Suggested Citation

  • Jihong Pang & Jinkun Dai & Yong Li, 2022. "An Intelligent Fault Analysis and Diagnosis System for Electromagnet Manufacturing Process Based on Fuzzy Fault Tree and Evidence Theory," Mathematics, MDPI, vol. 10(9), pages 1-18, April.
  • Handle: RePEc:gam:jmathe:v:10:y:2022:i:9:p:1437-:d:801188
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    References listed on IDEAS

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    2. Haikun Shang & Junyan Xu & Zitao Zheng & Bing Qi & Liwei Zhang, 2019. "A Novel Fault Diagnosis Method for Power Transformer Based on Dissolved Gas Analysis Using Hypersphere Multiclass Support Vector Machine and Improved D–S Evidence Theory," Energies, MDPI, vol. 12(20), pages 1-22, October.
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    4. Long-long Song & Tai-yong Wang & Xiao-wen Song & Lei Xu & De-gang Song, 2015. "Research and Application of FTA and Petri Nets in Fault Diagnosis in the Pantograph-Type Current Collector on CRH EMU Trains," Mathematical Problems in Engineering, Hindawi, vol. 2015, pages 1-12, October.
    5. Osama Moaaz & Jan Awrejcewicz & Omar Bazighifan, 2020. "A New Approach in the Study of Oscillation Criteria of Even-Order Neutral Differential Equations," Mathematics, MDPI, vol. 8(2), pages 1-8, February.
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    Cited by:

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