Double-Layer Fuzzy enhanced Failure Mode and Effects Analysis Method for Automatic Train Operation System

Automatic Train Operation (ATO) is a vital part of the urban rail transit signaling system. When the ATO system breaks down, it will automatically lead to train relegation, and emergency stop or serious accidents will be caused due to reaction time or human misoperation. Therefore, the ATO system is one of the necessary systems to ensure the normal operation of trains. Failure Mode and Effects Analysis (FMEA) is important for ATO to find failure causes. However, FMEA has been two continual problems which is uncertainty and incomplete analysis of system. The problems will cause the accuracy of the evaluation to decline, and some important failure causes will be hidden. In this paper, we propose a novel method based on fuzzy logic to evaluate the risk in double-layer fuzzy enhanced FMEA. Firstly, ATO failure analyzer is applied to classify and score ATO failure causes. Secondly, we use expert scoring mechanism to fuzzily aggregate t multiple scoring opinions. And then the fuzzy aggregation of Severity (S), Occurrence (O) and Detection (D) is obtained. Finally, Fuzzy Risk Priority Number (FRPN) is obtained by fuzzy risk estimator The result shows that this proposed method can find out the potential failure causes which are same Risk Priority Number (RPN) value in traditional FMEA and improve the accuracy of finding main failure causes. The reliability of ATO system can be guaranteed.