Research on Wheel-flat recognition Algorithm for High-speed Train Based on High-order Spectrum Feature Extraction

ZHAO Rong; SHI Hongmei

doi:10.3901/JME.2017.06.102

Journal of Mechanical Engineering >

2017 , Vol. 53 >Issue 6: 102 - 109

DOI: https://doi.org/10.3901/JME.2017.06.102

Research on Wheel-flat recognition Algorithm for High-speed Train Based on High-order Spectrum Feature Extraction

ZHAO Rong ,
SHI Hongmei

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School of Mechanical， Electrical Control Engineering， Beijing Jiaotong University， Beijing 100044

Online published: 2017-03-20

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Abstract

With the increasing of train speed and axle load,the wheel flats occur more frequently. A detection method for wheel flats is proposed based on PSO-SVM,in which high-order spectrum is used to extract the features of the rail vibration responses when the train runs on the rail. A vehicle-track vertical coupling system and wheel flat are modeled and the rail dynamic responses are calculated with the condition of normal wheel and wheel flat. The two-dimensional contour and three-dimensional double spectrum diagrams are obtained by analyzing two kinds of rail vibration responses with high-order spectrum method. Six texture features of the 2D contour map,which are extracted from gray-gradient co-occurrence matrix,are combined with the train speed to detect whether there is a wheel flat by PSO-SVM. Then the peak value of the diagonal slice of the three-dimensional double spectrum map and the frequency of the inner spread of the two-dimensional contour map are added into PSO-SVM to recognize different wheel-flat levels. The results show that the detection accuracy of normal wheel and wheel flats can be up to 100% and the recognition accuracy of wheel flat different levels is 94.6%. Finally,the recognition accuracy are compared and analyzed between high-order spectrum and EMD methods which are used to extract the feature signals. For EMD method,the detection accuracy for wheel flats is 98.3%,and for different wheel flat levels is only 56.4%. The investigation shows the detection method based on high-order spectrum and PSO-SVM can be used to identify wheel flat and its levels effectively.

Key words： wheel flats; rail vibration responses; high-order spectrum; gray-gradient co-occurrence matrix; PSO-SVM

Cite this article

ZHAO Rong , SHI Hongmei . Research on Wheel-flat recognition Algorithm for High-speed Train Based on High-order Spectrum Feature Extraction[J]. Journal of Mechanical Engineering, 2017 , 53(6) : 102 -109 . DOI: 10.3901/JME.2017.06.102

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