Method for diagnosing switch faults based on deep learning model

Abstract

The invention provides a method for diagnosing switch faults based on a deep learning model. The method comprises the following steps of normalizing the real-time to-be-detected switch starting current data L; then, inputting the normalized current data into a trained self-organized encoder; enabling the self-organized encoder to compress the switch starting current data L, outputting hidden layer data, and recording the outputted data as data L'; inputting the data L' into a RBF (radial basis function) neural network obtained in step 10, wherein the output of the RBF neural network is the fault diagnosis type reflected by the data L. The method has the advantages that the self-organized encoder is serially connected with the RBF neural network to form a novel deep learning model, so as to intelligently identify the switch starting current data, and reach the purpose of automatically diagnosing the switch faults. The deep learning model has the advantages that the switch fault is automatically diagnosed, and the diagnosis accuracy is high.

Description

technical field [0001] The invention belongs to the technical field of mechanical fault diagnosis and artificial intelligence, and in particular relates to a method for fault diagnosis of a turnout based on a deep learning model. Background technique [0002] The turnout is the realization equipment that turns the train vehicle from one railway line to another. Because the turnout has the characteristics of large number, complex structure, short service life, limited train speed, low driving safety, and large maintenance and repair investment, it is called the three weak links of the track together with the curve and the joint. One of the main equipment for maintenance. [0003] Timely detection, accurate diagnosis and early warning of turnout failures can not only prevent major accidents, avoid casualties and property losses; Making full use of the potential of equipment can also avoid unnecessary economic losses caused by regular maintenance, improve equipment utilizatio...

AI Technical Summary

Problems solved by technology

This kind of fault diagnosis method that relies purely on the work experience, professional level, energy and sense of responsibility of technicians is prone to misjudgments and missed judgments, which seriously threatens the safety

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