A multi-parameter intelligent threshold criterion for a high-speed train

Abstract

The invention discloses a multi-parameter intelligent threshold criterion of a high-speed train. Firstly, the working condition parameters and the state monitoring data of the high-speed train are collected, and the state monitoring data are divided according to the working condition parameters. Then, the fuzzy kernel clustering is used to analyze the condition monitoring data, and the center coordinates and the distance within the class are obtained. At last, the central coordinate, the distance within the class and the regression relationship between the multi-parameters of the working condition are calculated, and then the threshold value under various working conditions are intelligently calculated, and the high-speed train is intelligently alerted. The method is simple and applicableto the determination of intelligent threshold of monitoring data of high-speed trains under off-design conditions.

Description

technical field [0001] The invention belongs to the field of monitoring and diagnosis, and in particular relates to a multi-parameter intelligent threshold criterion for high-speed trains. Background technique [0002] With the rapid development of my country's railways, high-speed trains have become an important symbol of the rise of China's high-end manufacturing industry. However, high-speed trains are typical complex electromechanical systems, which integrate components in multiple physical domains such as mechanics, electricity, gas, and heat in a distributed and networked manner. complication. The maintenance of high-speed trains generally adopts a labor-intensive planned maintenance system regardless of cost and safety, which has become a bottleneck restricting the development and even export of high-speed trains in my country. For this reason, the railway maintenance and support department specifically proposed that future maintenance methods should be based on the ...

AI Technical Summary

Problems solved by technology

The main reason is that high speed usually works in the harsh environment of high speed, strong vibration and high stress, and it is difficult for a single threshold index to adapt to changes in working conditions

If the threshold is too high, the alarm can only be issued at the limit of the maximum speed, which will cause a large false alarm rate and fail to achieve real-time early warning and alarm.

If the threshold is too low, although it can adapt to low-speed working conditions, once it works at high speed, the normal state will be mistaken for a fault, which will cause a lot of waste of maintenance resources, and cause panic among personnel, affecting normal work.

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