Abstract
In this paper, a fault diagnosis method of train wheel based on empirical mode decomposition (EMD) generalized energy is proposed. First, EMD is applied to rail vibration signal to obtain the intrinsic mode functions (IMFs) and weight coefficients of each IMF are calculated. Then, quantitative value of EMD generalized energy is determined by calculating weighted sum of IMFs’ energy. Finally, the security domain threshold of EMD generalized energy is determined to distinguish faulted wheel. Experiment results by using simulation data showed that the proposed method can distinguish normal and faulted wheels and the accuracy reached above 90%.
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Acknowledgements
This work is supported by National Key R&D Program of China under Grant (2017YFB1201201).
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Chen, Y., Wang, X., Zhang, Y., Xing, Z. (2018). Fault Diagnosis of Train Wheels Based on Empirical Mode Decomposition Generalized Energy. In: Jia, L., Qin, Y., Suo, J., Feng, J., Diao, L., An, M. (eds) Proceedings of the 3rd International Conference on Electrical and Information Technologies for Rail Transportation (EITRT) 2017. EITRT 2017. Lecture Notes in Electrical Engineering, vol 483. Springer, Singapore. https://doi.org/10.1007/978-981-10-7989-4_2
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DOI: https://doi.org/10.1007/978-981-10-7989-4_2
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