Fault diagnosis-based rail transit vehicle bearing residual life prediction method

Abstract

The invention discloses a fault diagnosis-based rail transit vehicle bearing residual life prediction method. The method includes the following steps that: S100, multi-angle feature extraction and fusion are performed; S200, cyclostationary theory-based fault diagnosis is performed; S300, multi-variable model training is performed, so that multi-variable model-based fault isolation is realized; and S400, based on a semi-supervised algorithm, a BP neural network algorithm and a support vector regression algorithm are used in combination to perform fault diagnosis-based residual life prediction. With the fault diagnosis-based rail transit vehicle bearing residual life prediction method of the invention adopted, fault detection, fault isolation and residual life prediction at the early stage of the fault of a bearing are realized, and a basis is provided for the formulation of vehicle bearing maintenance decision making.

Description

technical field [0001] The invention relates to the fields of fault diagnosis and remaining life prediction of rail transit vehicle bearings. More specifically, it relates to a method for predicting the remaining life of rail vehicle bearings based on fault diagnosis. Background technique [0002] The rapid development of rail transit has put forward higher requirements for the safety and reliability of vehicles. Many operating lines are overloaded during morning and evening peak hours, which requires that each key system of the train must be safe and reliable, and must not be faulty or fail to operate. Bearing is one of the indispensable components in rail transit, and it is also the most vulnerable component, and its effectiveness directly leads to the safety of train operation. The complex and time-varying operating environment: load, track smoothness, temperature, etc., have a great impact on the health of the bearing. When a fault occurs in a certain part of the bear...

AI Technical Summary

Problems solved by technology

When a fault occurs in a certain part of the bearing, a chain reaction will occur, which may cause damage to the related systems of the vehicle, or cause the suspension of the vehicle or even casualties

[0003] In the existing remaining life prediction research, less consideration is given to the impact of failure types on remaining life prediction

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