Abstract
In this paper, fisher discriminant analysis (FDA) is used for fault isolation and diagnosis in rail vehicle suspension systems. The suspension systems are equipped with acceleration sensors in the corners of the car body and the two bogies. The faults considered are the lateral damper faults and the lateral spring faults in suspension systems. FDA provides an optimal projection space on the basis of the training data including the fault data and normal data to classify the test data. A vehicle model is built by SIMPACK/MATLAB software with real parameters to obtain the simulation data and the effectiveness of the proposed method is demonstrated by simulation.
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Acknowledgment
This work is partly supported by Chinese 863 program (Contract No. 2011AA110503-6) and Ph.D. Programs Foundation of Ministry of Education of China (grant number: 20110009120037).
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Wei, X., Wu, S., Ding, J., Jia, L., Sun, Q., Yuan, M. (2014). Fault Diagnosis for Rail Vehicle Suspension Systems Based on Fisher Discriminant Analysis. In: Jia, L., Liu, Z., Qin, Y., Zhao, M., Diao, L. (eds) Proceedings of the 2013 International Conference on Electrical and Information Technologies for Rail Transportation (EITRT2013)-Volume II. Lecture Notes in Electrical Engineering, vol 288. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-53751-6_34
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DOI: https://doi.org/10.1007/978-3-642-53751-6_34
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