Locomotive and vehicle abnormal axle temperature diagnostic method and system

Abstract

The present invention provides a locomotive and vehicle abnormal axle temperature diagnostic method and system. Temperature time-domain features of a plurality of associated measurement points at a plurality of time windows are combined to a feature set, the feature set is subjected to k-means clustering, the feature position difference is determined through the k-means clustering to determine whether there is an isolated measurement point or not, if yes, the maximum radius of a cluster where normal measurement points belong to is taken as a radius of neighborhood, the number of the temperature time-domain features corresponding to a single associated measurement pint is taken as the minimum neighborhood density, the feature set is subjected to DBSCAN clustering according to the radius ofneighborhood and the minimum neighborhood density to determine whether the distribution density has obvious difference or not. If the results of the k-means clustering and the DBSCAN clustering of thetemperature time-domain features corresponding to a certain associated measurement point have the position difference and distribution density difference at the same time, it is determined that the associated measurement points have temperature anomaly. The method and the system provided by the invention effectively improve the locomotive and vehicle abnormal axle temperature diagnosis accuracy and correspondingly reduce the diagnosis misjudgment rate.

Description

Technical field [0001] The present invention relates to the technical field of fault diagnosis of rolling stock, and more specifically, to a method and system for diagnosing abnormal axle temperature of rolling stock. Background technique [0002] Temperature is the most direct parameter reflecting the thermal state of the bearing, so the abnormal temperature rise of the bearing can be diagnosed based on the temperature signal, and then the hot shaft failure can be warned. Bearing wear degradation may cause shaft temperature to rise, and changes in bearing speed, load, and ambient temperature under normal operating conditions can also cause bearing temperature rise. Bearing temperature information can effectively characterize its health, and the uncertainty of the cause of bearing temperature rise is the difficulty of bearing fault diagnosis based on temperature signals. [0003] In the prior art, bearing fault diagnosis based on temperature signals mainly includes two types of im...

AI Technical Summary

Problems solved by technology

[0005] In order to overcome the problems of the prior art in the method of bearing fault diagnosis based on temperature signals, due to the diversity and complexity of temperature rise factors, it is difficult to ensure the accuracy of diagnosis results and the situation that misjudgment cannot be effectively avoided, and provides Method and system for diagnosing abnormal axle temperature of rolling stock

Images