A fault location strategy based on information fusion and CODAS algorithm under epistemic uncertainty

Application of new technology in modern systems not only substantially improves the performance, but also presents a severe challenge to fault location of these systems. This paper presents a new fault location strategy for maintenance personnel to recover them based on information fusion and improved CODAS algorithm. Firstly, a fault tree is adopted to develop the failure model of a complex system, and failure probability of components is determined by expert evaluations to handle the uncertainty problem. Moreover, a fault tree is converted into an evidence network to obtain importance degrees, which are used to construct a diagnostic decision table together with the risk priority number. Additionally, these results are updated to optimize the maintenance process using sensor information. A novel dynamic location strategy is designed based on interval CODAS algorithm and optimal fault location strategy can be obtained. Finally, a real system is analyzed to demonstrate the feasibility of the proposed maintenance strategy.