Abstract
Motor current signature analysis for bearing fault is an important diagnosis method. However, the current signature for bearing fault is very weak and always buried in heavy noise. In order to detect bearing fault effectively, a new way that analyzing motor speed signature is proposed. The speed expression is deduced, and the speed signature is analyzed when the bearing fault occurs. Simulation researches are conducted in MATLAB, with considering the effect of noise interference on current and speed. Both of the two signals are used to detect the bearing fault, respectively, and the simulation results are compared. The obtained results validate that the motor speed signature is more effective for bearing fault detection than current signature.
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Acknowledgment
The research work was supported by National Natural Science Foundation of China under Grant No. 51279020. The support is greatly appreciated.
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Cheng, G., Qiu, C., Wu, X., Ma, J. (2016). Research on the Speed Signature of Induction Motor Bearing Fault. In: Jia, L., Liu, Z., Qin, Y., Ding, R., Diao, L. (eds) Proceedings of the 2015 International Conference on Electrical and Information Technologies for Rail Transportation. Lecture Notes in Electrical Engineering, vol 377. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-662-49367-0_3
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DOI: https://doi.org/10.1007/978-3-662-49367-0_3
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