Railway Turnout Fault Diagnosis Based on Support Vector Machine

You Min He; Hui Bing Zhao; Jian Tian; Meng Qi Zhang

doi:10.4028/www.scientific.net/AMM.556-562.2663

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HomeApplied Mechanics and MaterialsApplied Mechanics and Materials Vols. 556-562Railway Turnout Fault Diagnosis Based on Support...

Railway Turnout Fault Diagnosis Based on Support Vector Machine

Abstract:

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%.

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Periodical:

Applied Mechanics and Materials (Volumes 556-562)

Pages:

2663-2667

DOI:

https://doi.org/10.4028/www.scientific.net/AMM.556-562.2663

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Online since:

May 2014

Authors:

You Min He*, Hui Bing Zhao, Jian Tian, Meng Qi Zhang

Keywords:

Fault Diagnosis, Grid Search, SVM, Turnout

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* - Corresponding Author

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