The maintenance efficiency of Chinese railway turnout is closely related to the accuracy of its fault diagnosis method. A proper method will provide great help to railway staff in maintaining turnouts. The research introduced in this paper built a model based on Support Vector Machine (SVM) and Grid Search and later than tested its effect with the data from experiments. Result of that test shows that the method can achieve a diagnosis accuracy as high as 98.33%.
Railway Turnout Fault Diagnosis Based on Support Vector Machine
Applied Mechanics and Materials ; 556-562 ; 2663-2667
23.05.2014
5 pages
Aufsatz (Zeitschrift)
Elektronische Ressource
Englisch
Fault Diagnosis , Grid Search , Turnout , SVM
Railway turnout fault diagnosis method and system based on machine learning
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