Health status assessment method of high-speed railway catenary based on set pair analysis and evidence theory

Abstract

The invention discloses a method for evaluating the health state of high-speed railway catenary based on set pair analysis and evidence theory, which includes the following steps: determining the constant weight of each evaluation index in the sub-indicator layer by combining the variation coefficient method and the analytic hierarchy process; The degree of deterioration is given a corresponding variable weight; the set pair analysis method is used to determine the degree of connection between each evaluation index in the sub-indicator layer and each health status level, and it is assigned as a basic probability; then the revised basic probability The distribution is fused to obtain the evaluation results; finally, the maximum membership degree principle and the confidence criterion are used to judge the health status of the catenary. The invention not only can effectively identify the health state of catenary, but also has more accurate assessment results and greater discrimination between state levels.

Description

technical field [0001] The invention relates to the field of health status assessment of high-speed railway catenary, in particular to a method for assessing the health status of high-speed railway catenary based on set pair analysis and evidence theory. Background technique [0002] The catenary is an important part of the electrified railway traction power supply system. It is a special form of transmission line that supplies power to trains. Its operating performance directly affects the power supply stability of the traction power supply system. The health of the catenary plays a vital role in ensuring the safe operation of high-speed railways. Therefore, using the high-speed railway power supply safety detection and monitoring system (6C system) to detect the catenary to improve the accuracy of catenary health status assessment will help the railway department to accurately grasp the health status of the catenary, so as to reasonably formulate maintenance. The plan is ...

AI Technical Summary

Problems solved by technology

[0003] At present, the high-speed railway catenary still judges whether it is faulty or not based on whether the detection data exceeds the limit. The evaluation results obtained in this way are simple and cannot reflect the change process of the catenary health status.

Wu Junyong et al. used the fault tree analysis method, event tree analysis method, and reliability theory to establish the reliability model of the entire catenary system using years of fault records of catenary equipment. Safe Operation Requirements

Based on the Hilbert-Huang transformation, Shi Bin et al. performed feature extraction on the detection data of the catenary to evaluate the operation status of the catenary, but could only evaluate the overall status of the catenary, and could not determine the health status of a certain position of the catenary. , there are certain limitations

He Zhengyou et al. used fuzzy comprehensive evaluation methods, gray clustering, cloud models, etc. to evaluate the health status of the catenary. These methods were insufficient in dealing with information uncertainty and information fusion, and directly weighted the evaluation indicators of catenary status. Fusion, does not fully consider the information fusion of each evaluation index in the index layer, and it is easy to cause errors in the evaluation results of catenary health status when the status of each evaluation index is greatly different

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