Affiliations: [a] School of Automation and Electrical Engineering, Lanzhou Jiaotong University, Lanzhou, Gansu 730070, China | [b] Rail Transit Electrical Automation Engineering Laboratory, Lanzhou Jiaotong University, Lanzhou, Gansu 730070, China | [c] School of Finance, Central University of Finance and Economics, Beijing 102206, China
Correspondence:
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Corresponding author: Hongsheng Su, School of Automation, Electrical Engineering Lanzhou Jiaotong University, 88 West Anning Road, Lanzhou, Gansu 730070, China. E-mail: shsen@163.com.
Abstract: In view of the defects of traditional analysis methods on railway signal equipments risk evaluation such as few data, and poor information, and as well as low precision, in this paper, a novel risk assessment method is proposed for railway signal devices based on fuzzy grey theory, which effectively integrates variable weight synthesis method into fuzzy-grey theory to facilitate more judicious decision-making. In the method, we firstly implement Failure Mode Effects and Criticality Analysis (FMECA) on evaluation objection using fuzzy level of the severity degree (S), and the occurrence degree (O), and also the detection degree (D) of the signal system. And the defuzzifization is then performed on each fuzzy grade to get fuzzy brittleness coefficient. Based on it, according to grey theory, the grey correlation coefficients of S, and O, and as well as D can be easily obtained. Moreover, the weight of each grey correlation coefficient can be obtained applying variable weight principle. Eventually, the grey correlation degree of each fault mode can be obtained adding all products of the relevant correlation coefficient multiplied by its corresponding weight. By application in ZPW-2000A track circuit, the results show that the risk assessment method based on RPN applying fuzzy grey theory is more precise than the traditional RPN and fuzzy RPN, and such that it is more effective and reasonable.
