Affiliation:
1. College of Civil Aviation Nanjing University of Aeronautics and Astronautics Nanjing China
Abstract
AbstractThis paper proposed a method for the reliability analysis of systems characterized by fuzzy failure probabilities and intricate failure behaviors, while retaining the fuzzy information throughout the analysis process. Specifically, we introduced a combinational modeling method that integrates generalized stochastic Petri nets (GSPN) and dynamic fault trees (DFT) to capture the dynamic failure behaviors and address the limitations of DFT modeling. This combinational approach is capable of capturing more sophisticated failure behaviors, such as competing failures and global failure propagation patterns. Furthermore, we propose an Monte Carlo technique based on endpoint sampling to enable quantitative analysis of GSPN‐based composite models, which preserves the fuzzy fault information of the system. Finally, we demonstrate the effectiveness of the proposed method through an example of a flight control system.
Funder
Civil Aviation Administration of China
National Natural Science Foundation of China
Fundamental Research Funds for the Central Universities
Subject
Management Science and Operations Research,Safety, Risk, Reliability and Quality
Cited by
1 articles.
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