Health Status Evaluation of Catenary Based on Normal Fuzzy Matter-Element and Game Theory

Abstract

At present, there is no unified standard for the health status evaluation of electrified railway catenary in China. The current catenary evaluation model only considers quantitative detection indicators, without qualitative indicators such as weather, which is one-sided to some extent. Thus, an improved catenary status evaluation model is constructed with both quantitative indicators and qualitative indicators. In this evaluation model, the normal fuzzy matter-element method is used to determine the correlation value of each grade, and the weighted average principle is used to re-determine the status grade of catenary when the maximum correlation principle fails. Meanwhile, entropy weight method and particle swarm optimization algorithm to optimize analytic hierarchy process method are combined to improve the shortcomings of single weight method, and game theory is used to determine the subjective and objective weight coefficients, so as to reduce the influence of subjective experience. Select a Chinese railway catenary in 2018 as an example for verification analysis, the results show that the model constructed in this paper can effectively help professionals to make correct judgments on the health status of catenary, and provide a new idea and method for the comprehensive evaluation of the catenary operation status, which has certain practicability.