Systems Engineering and Electronics

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Novel dynamic evidential Petri net for system reliability analysis

Wensheng Peng1,2, Jianguo Zhang1,3,*, and Jinyang Zhang1,3   

  1. 1. School of Reliability and Systems Engineering, Beihang University, Beijing 100191, China;
    2. China Aero-Polytechnology Establishment, Aviation Industry Corporation of China, Beijing 100028, China;
    3. Science and Technology on Reliability and Environment Engineering Laboratory, Beihang University, Beijing 100191, China
  • Online:2017-10-25 Published:2010-01-03


This paper proposes a novel dynamic Petri net (PN) model based on Dempster-Shafer (D-S) evidence theory, and this improved evidential Petri net (EPN) model is used in knowledge inference and reliability analysis of complex mechanical systems. The EPN could take epistemic uncertainty such as interval information, subjective information into account by applying D-S evidence quantification theory. A dynamic representation model is also proposed based on the dynamic operation rules of the EPN model, and an improved artificial bee colony (ABC) algorithm is employed to proceed optimization calculation during the complex systems’ learning process. The improved ABC algorithm and D-S evidence theory overcome the disadvantage of extremely subjective in traditional knowledge inference efficiently and thus could improve the accuracy of the EPN learning model. Through a simple numerical case and a satellite driving system analysis, this paper proves the superiority of the EPN and the dynamic knowledge representation method in reliability analysis of complex systems.