Abstract
This paper presents a dynamic diagnostic strategy based on reliability analysis and distance-based VIKOR with heterogeneous information. Specifically, the proposed method uses a dynamic fault tree (DFT) to describe the dynamic fault characteristics and evaluates the failure rate of components using interval numbers to deal with the epistemic uncertainty. Furthermore, DFT is mapped into a dynamic evidential network (DEN) to calculate some reliability parameters and these parameters together with test cost constitute a decision matrix. In addition, a dynamic diagnostic strategy is developed based on an improved VIKOR algorithm and the previous diagnosis result. This diagnosis algorithm determines the weights of attributes based on the Entropy concept to avoid experts’ subjectivity and obtains the optimal ranking directly on the original heterogeneous information without a transformation process, which can improve diagnosis efficiency and reduce information loss. Finally, the performance of the proposed method is evaluated by applying it to a train-ground wireless communication system. The results of simulation analysis show the feasibility and effectiveness of this methodology
Highlights
The application of high technology to the engineering system has significantly improved the performance of modern systems and at the same time greatly increased the complexity of the systems structure
High reliability makes it extremely difficult to obtain complete fault data because these systems may still be in the early life cycle, which results in the epistemic uncertainty
Motivated by the problems mentioned above, this paper proposes a dynamic diagnostic strategy based on reliability analysis and dis
Summary
The application of high technology to the engineering system has significantly improved the performance of modern systems and at the same time greatly increased the complexity of the systems structure. The difficult to determine the corresponding membership function of each former can resort to fault mode and effect analysis and the latter needs language value, and this diagnosis algorithm was a single attribute to obtain lots of fault data, which is almost impossible to estimate decision making problem To overcome these limitations, multiple at- precisely the failure rates of the basic events in the practical engineertributes decision-making was used in [7, 20]. Traditional DFT assumes that the failure rates of the components are expressed in defined values is inadequate to deal with epistemic uncertainty To this end, the failure rates of the basic events in DFT are considered as interval numbers in this paper and a new DFT solution is proposed to calculate the reliability results by mapping a DFT into a DEN. The upper and lower bounds of the component’s failure probability is equivalent to the BPA of component i in the DEN:
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