Research on strong and weak evaluation method of air brake for intelligent driving heavy haul train - WANG Feikuan; JIANG Jie; ZHANG Zhengfang; LUO Yuan (机车电传动)
In the process of circulating air brake control of intelligent driving heavy haul train with the formation of 3+0, because the magnitude of air braking force is affected by various factors such as railway line conditions, vehicle load, friction characteristics of brake shoes, differences in pipelines, and intermittent working characteristics of air brakes, it is difficult to accurately plan and control trains, even causing potential safety hazards. To solve this problem, this paper proposed a prediction method for the strong and weak of air braking force based on IPSO-SVM (Improved Particle Swarm Optimization-Support Vector Machine). IPSO was used to optimize the parameters of SVM. The main factors affecting the magnitude of air braking force were used as the input of SVM to evaluate the strong and weak of air braking force, and the analysis and verification were carried out based on the measured data of Shenmu-Shuozhou railway. The results show that the prediction accuracy of the proposed method can reach more than 90%, which verifies the method is rational and effective, having good and practical value in engineering application.