A detection method for the crack fault of the bogie of maglev train

Abstract

The invention discloses a method for detecting a crack fault of a bogie of a maglev train. The method comprises the following steps: S1, collecting a vibration acceleration signal of a bogie of a maglev train by a sensor and acquiring a modal parameter of the bogie of the maglev train in a running state from the vibration acceleration signal; S2, carrying out the principal component analysis (PCA)on the modal parameter obtained in the S1 and extracting a principal component vector sensitive to a crack fault of the maglev train bogie; S3, establishing a support vector machine (SVM) model and carrying out SVM training on the principal component vector extracted in the S2 to obtain a classification surface of the principal component vector point sensitive to a crack fault of the maglev trainbogie; and S4, according to the position of the principal component vector obtained in the S2 in the classification surface in the S3, determining whether the maglev train bogie has a crack fault. Therefore, whether the bogie has a crack fault is determined accurately. The method has characteristics of high sensitivity, high precision and high efficiency.

Description

technical field [0001] The invention relates to the technical field of maglev trains, in particular to a detection method for a crack fault on a bogie of a maglev train. Background technique [0002] If the state of the bogie can be monitored during the operation of the maglev train, and an automatic alarm and prediction can be realized for abnormal situations, the safety performance of the maglev train can be improved. Traditional train maintenance relies on workers in the maintenance depot or platform to judge whether there is any abnormality in the bogie by observation or percussion and listening. However, this method is prone to omissions and takes time and effort. [0003] The fault diagnosis and monitoring of maglev train bogie cracks belong to the category of structural damage. The research work of structural damage diagnosis abroad can be roughly divided into three stages: the early stage is the exploration stage, which explores the causes of defects and repair metho...

AI Technical Summary

Problems solved by technology

However, there are system and measurement errors and the sensitivity coefficients of each modal frequency to cracks are different, so it is difficult to classify and identify faults with the traditional threshold method. The incentive is random, and the response is often random

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