Fault prediction method and device for rail transit power supply equipment

Abstract

The invention discloses a fault prediction method and device for rail transit power supply equipment. An LSTM + SVM model is firstly adopted to predict a power supply system fault. The method comprises the following steps: firstly, generating a power supply system fault prediction model by using an LSTM algorithm and historical data of system equipment, then carrying out denoising and standardization processing on current data of the system equipment, then inputting the processed data into the prediction model to obtain prediction data of target equipment, and finally classifying the data output by the prediction model by using an SVM model, and outputting an equipment state result. According to the method and device, the advantages that the long-term and short-term memory model can perform long-term prediction and the support vector machine has good nonlinear classification are combined, the LSTM + SVM model is firstly adopted to predict the fault of the power supply system, and a method for accurately predicting the fault is established for the rail transit power supply system; and the stability and the safety of a rail transit power supply system can be effectively improved.

Description

technical field [0001] The invention relates to the field of rail transit power system fault prediction, in particular to a method for fault prediction of rail transit supply equipment based on an LSTM neural network model. Background technique [0002] With the rapid development of my country's high-speed rail and urban rail transit, the scale of trains and the frequency of train transportation continue to increase, and the failure of the power supply system is more and more harmful to the social economy and personal safety. The rail transit power supply system is facing severe challenges. . Accurate and rapid prediction of rail transit power supply system failures is an effective way to avoid power supply system failures and a series of serious consequences. It is of great significance to study the fault prediction method of rail transit power supply equipment with high reliability and fast prediction speed to ensure the safety and economy of the entire rail transit power ...

AI Technical Summary

Problems solved by technology

However, this method can only analyze the type of failure and the cause of the failure, and cannot predict the failure. It belongs to the mode of diagnosis after failure.

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