Modal intervals-based high-speed train bogie fault diagnosis method

Abstract

A modal intervals-based high-speed train bogie fault diagnosis method includes the steps of 1, acquiring a high-speed train bogie vibration signal; 2, preprocessing the high-speed train bogie vibration signal; 3, subjecting the high-speed train bogie vibration signal to modal interval valuing; 4, subjecting the high-speed train bogie vibration signal to EMD (experience modal decomposition); 5, subjecting the high-speed train bogie vibration signal to feature extraction; 6, constructing and training an initial interval neural network model; and 7, performing high-speed train bogie fault diagnosis. Uncertainty in bogie vibration signals is processed by the modal interval method, and high-speed train bogie faults are diagnosed by a classified recognition method of the interval neural network model; the uncertainty in the high-speed train bogie fault diagnosis is handled by the modal interval method, and reliability of fault diagnosis results is greatly improved. The method is applicable to the fault diagnosis for high-speed train bogies.

Description

technical field [0001] The invention relates to the field of fault diagnosis of high-speed trains, in particular to a fault diagnosis method for bogies of high-speed trains. Background technique [0002] The bogie plays the role of guidance, bearing, and vibration reduction in the operation of high-speed trains. It is also the final performer of traction and braking, and is a key component of high-speed trains. The bogie is subjected to frequent random dynamic loads during the operation of high-speed trains, which may cause various failures in key parts of the bogie structure, and the occurrence of failures will lead to increased vibration of various parts of the high-speed train, reduced operating quality, and even lead to Serious accidents such as derailment and rollover. Therefore, it is of great significance to carry out research on the performance detection and fault diagnosis of high-speed train bogies for the safe and reliable operation of high-speed trains. [0003...

AI Technical Summary

Problems solved by technology

Due to the complexity of the high-speed train bogie structure and the uncertainty and chance of various influencing factors in the operating state, the measurement results of the vibration signal of the high-speed bogie will also be uncertain and random, and the traditional diagnostic model methods are few. respond to these uncertainties, which will lead to a less reliable diagnosis

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