Intelligent Evaluation of Ball Bearing Health Degradation Using Wavelet Packet Transform and k-Nearest Neighbor
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Publisher
Springer Nature Singapore
Link
https://link.springer.com/content/pdf/10.1007/978-981-19-2188-9_34
Reference24 articles.
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3. Goyal D, Choudhary A, Pabla BS, Dhami SS (2019) Support vector machines based non-contact fault diagnosis system for bearings. J Intell Manuf. https://doi.org/10.1007/s10845-019-01511-x
4. Liu Z, Cao H, Chen X, He Z, Shen Z (2013) Multi-fault classification based on wavelet SVM with PSO algorithm to analyze vibration signals from rolling element bearings. Neurocomputing 99:399–410. https://doi.org/10.1016/j.neucom.2012.07.019
5. Rajeswari C, Sathiyabhama B, Devendiran S, Manivannan K (2014) Bearing fault diagnosis using wavelet packet transform, hybridnPSO and support vector machine. Procedia Eng. 97:1772–1783. https://doi.org/10.1016/j.proeng.2014.12.329
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