Artificial Intelligence


Belief Reliability Analysis and Its Application

Authors: Haoyang Zheng, Likang Yin, Tian Bian, Yong Deng

In reliability analysis, Fault Tree Analysis based on evidential networks is an important research topic. However, the existing EN approaches still remain two issues: one is the final results are expressed with interval numbers, which has a relatively high uncertainty to make a final decision. The other is the combination rule is not used to fuse uncertain information. These issues will greatly decrease the efficiency of EN to handle uncertain information. To address these open issues, a new methodology, called Belief Reliability Analysis, is presented in this paper. The combination methods to deal with series system, parallel system, series-parallel system as well as parallel-series system are proposed for reliability evaluation. Numerical examples and the real application in servo-actuation system are used to show the efficiency of the proposed Belief Reliability Analysis methodology.

Comments: 24 Pages.

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Submission history

[v1] 2016-10-07 00:22:44

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