Username   Password       Forgot your password?  Forgot your username? 

 

Fuzzy Fault Tree Analysis based on Interpretive Structure Model and Binary Connection Numbers

Volume 15, Number 1, January 2019, pp. 45-55
DOI: 10.23940/ijpe.19.01.p5.4555

Honghua Sun, Hongxia Chen, Qingyang Li, and Xudong Chen

School of Mechanical Engineering, Inner Mongolia University of Technology, Hohhot, 010051, China

(Submitted on October 8, 2018; Revised on November 17, 2018; Accepted on December 15, 2018)

Abstract:

Building a fault tree and calculating the sequence of bottom events importance degree are key steps in fault diagnosis. Two improvements are made to the fuzzy fault tree in this study. The first is building the fault tree using Interpretive Structure Modeling (ISM) technology. The second is transforming triangular fuzzy numbers into binary connection numbers (BCN) through the uncertainty theory of set pair analysis, where the certainty coefficient is determined by the median of the triangular fuzzy number and the uncertainty coefficient is determined by the interval value described by the upper and lower limitations. The formula of failure probability of the top event and the formula of probability importance of the bottom event are deduced with the binary connection number. This method reduces the calculation amount. A case study is carried out to verify the feasibility and effectiveness of the method.

 

References: 22

      1. J. X. Hu, L. Y. Xie, Y. Xin, X. Bai, and E. J. Bai, “FMECA-based FTA Automatic Fault Tree Drafting,” Journal of Harbin Engineering University, Vol. 38, No. 7, pp. 1162-1166, July 2017
      2. Z. H. Du and C. C. Di, “Mechanism Product Integrated Study of FTA and FMECA based on VB and ACCESS,” Computer Applications Technology, Vol. 36, No. 10, pp. 34-38, October 2009
      3. J. F. Tao, S. P. Wang, and S. P. Du, “Fault Diagnosis for Clutch and Brake based on Expert System,” Journal of Beijing University of Aeronautics and Astronautics, Vol. 26, No. 6, pp. 663-665, December 2000
      4. W. H. Xu and Y. P. Zhang, “A Fault Tree Auto-Modeling Method based on Avionics System Architecture Model,” Computer Engineering & Science, Vol. 39, No. 12, pp. 2269-2277, December 2017
      5. P. Yang, “Research on Method of Fault Tree Created Automatically based on FMECA,” Computer and Modernization, No. 12, pp. 193-196, December 2009
      6. M. Y. Huang, O. Wei, and J. Hu, “Fault Tree Generation based on Fault Configuration,” Computer Science, Vol. 44, No. 2, pp. 182-191, February 2017
      7. M. Li, C. P. Cao, and Y. Sun, “Fault Diagnosis for Clutch and Brake based on Expert System,” Forging Stamping Technology, Vol. 42, No. 12, pp. 163-169, December 2017
      8. W. H. Gu and S. G. Wang, “Collapse Risk Analysis for the Loess-featured Tunnels in Railway Construction based on ISM and Fuzzy Fault Tree Method,” Computer Science, Vol. 44, No. 2, pp. 182-191, October 2017
      9. R. S. Sun and X. Zhan, “Analysis on Influence Factors of Controlled Flight into Terrain of General Aviation based on ISM-CRITIC Method,” Journal of Safety Science and Technology, Vol. 14, No. 1, pp. 129-135, January 2018
      10. Y. M. Wei, X. S. Gan, W. W. You, and M. L. Jiang, “Inducement Relationship Analysis of Controlled Flight into Terrain based on ISM Model,” Fire Control & Command Control, Vol. 43, No. 2, pp. 172-176, February 2018
      11. J. H. Xia and H. J. Wang, “Fault Cause Analysis of Complex Manufacturing System based on DEMATEL-ISM,” Journal of Beijing Information Science & Technology University, Vol. 33, No. 1, pp. 31-47, February 2018
      12. H. Z. Huang and Y. F. Li, “A New Ordering Method of based Events in Fault Tree Analysis,” Quality and Reliability Engineering International, Vol. 28, No. 3, pp. 297-305, March 2012
      13. Z. S. Xu, “Study on Method for Triangular Fuzzy Number based Multi-attribute Decision Making with Preference Information on Alternatives,” Systems Engineering and Electronics, Vol. 124, No. 18, pp. 9-12, August 2002
      14. C. B. Li and Z. Y. Pan, “Fuzzy Comprehensive Assessment of Power Enterprise R&D Risk based on Triangular Fuzzy Number,” Journal of Chongqing University of Technology (Natural Science), Vol. 31, No. 1, pp. 143-151, January 2017
      15. C. Q. Zhao, J. W. Zhang, Y. Sun, and Y. Y. Zhang, “Analysis and Application of Fire and Explosion Fault Tree in Hydrocracking Unit based on Triangular Fuzzy Number,” Safety and Environmental Engineering, Vol. 24, No. 6, pp. 119-122, November 2017
      16. X. C. Li, Q. L. Liu, and L. S. Pei, “Analysis on Danger Sources of Mine Gas Explosion based on Fuzzy Fault Tree,” Coal Engineering, Vol. 46, No. 5, pp. 93-96, May 2014
      17. L. Yang and G. H. Qi, “A Group Decision Making Method with Interval-Valued Triangular Fuzzy Attribute and Weight,” Fuzzy Systems and Mathematics, Vol. 31, No. 1, pp. 179-186, February 2017
      18. X. M. Liu, K. Q. Zhao, and C. B. Wang, “New Multiple Attribute Decision-Making Model with Triangular Fuzzy Numbers based on Connection Numbers,” Systems Engineering and Electronics, Vol. 31, No. 10, pp. 2399-2403, October 2009
      19. X. M. Liu and K. Q. Zhao, “Triangular Fuzzy Number Multi-Attribute Decision-Making with the Attribute Weight Unknown based on Connection Number,” Fuzzy Systems and Mathematics, Vol. 31, No. 2, pp. 95-106, April 2017
      20. G. D. Lu and C. Wu, “Interval Number Multiple-Attribute Decision-Making based on Adjoint Functions of Connection Number,” Fuzzy Systems and Mathematics, Vol. 32, No. 2, pp. 182-190, February 2018
      21. Y. L. Zhao and K. Q. Zhao, “Fault Diagnosis of Turbine based on Multiple Dual Connection Number,” Modern Manufacturing Engineering, No. 2, pp. 155-160, February 2016
      22. Y. L. Wang, “Systems Engineering,” China Machine Press, Beijing, 2008

           

          Please note : You will need Adobe Acrobat viewer to view the full articles.Get Free Adobe Reader

           
          This site uses encryption for transmitting your passwords. ratmilwebsolutions.com