A method for detecting abnormal temperature of rail vehicle components

Abstract

The invention discloses a method for detecting abnormal temperature of rail vehicle components. According to the needs of driving safety, one or more components are determined as the object to be detected with abnormal temperature. Construct a lightweight gradient hoisting machine model to establish the importance of various driving parameters of the vehicle for the temperature prediction of a single object to be detected; based on the characteristics of the temperature rise lag speed, determine the input time step of the characteristics required for predicting the temperature; combined with the temperature to be detected The spatial position distribution of the components and the Pearson coefficient analysis of the relationship between the same vehicle components, based on the concept of similar components to be detected, simultaneously predict the temperature of multiple objects to be detected; build a prediction model, use the convolutional network to predict the time series signals, and get The residual value of the real temperature and the predicted temperature; the obtained residual value is described in two-dimensional space according to the concept of similar components, and the abnormal detection of the residual is carried out by using the isolated forest method, and the early warning of the component temperature abnormality in the process of rail vehicle running .

Description

technical field [0001] The invention belongs to the field of rail vehicle abnormality detection and relates to a temperature abnormality detection method of rail vehicle components. Background technique [0002] In recent years, my country's rail vehicles have continued to develop, and the safety and reliability of railways have continued to receive the attention of the entire industry. In the field of railways, Beijing Jiaotong University, Central South University, Southwest Jiaotong University, and CRRC Qingdao Sifang Research Institute have all conducted research on the safety of rail vehicles. [0003] Key components such as axles, bearings, and brake discs, as key components that affect driving safety, are subjected to complex excitations and changing working conditions, which will cause the temperature of the above-mentioned components to rise, and in severe cases will cause the above-mentioned components to fail, affecting driving safety. Therefore, predicting and mo...

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Problems solved by technology

[0006] In view of the problems mentioned in the background technology, the low prediction accuracy caused by the weak data processing ability of the current model, the small application range, and the slow positioning and training caused by the prediction of a single target, the present invention proposes a lightweight The gradient hoisting machine conducts auxiliary analysis on the data collected by the rail vehicle sensors, selects the input time step of the vehicle history data required to predict the temperature, and combines the spatial position distribution of each component to be detected and the Pearson coefficient to analyze the relationship between the corresponding components of the same row of vehicles , to establish a method for simultaneously predicting the temperature of multiple components

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