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Shock and Vibration
Volume 2018, Article ID 5063527, 29 pages
https://doi.org/10.1155/2018/5063527
Research Article

Rolling Bearing Fault Diagnosis Using Modified Neighborhood Preserving Embedding and Maximal Overlap Discrete Wavelet Packet Transform with Sensitive Features Selection

1School of Information and Control Engineering, China University of Mining and Technology, Xuzhou 221000, China
2IOT Perception Mine Research Center, China University of Mining and Technology, Xuzhou 221000, China
3School of Medicine Information, Xuzhou Medical University, Xuzhou 221000, China
4Institute of Electrodynamics and Microelectronics, University of Bremen, 28359 Bremen, Germany

Correspondence should be addressed to Enjie Ding; nc.ude.tmuc@deijne

Received 20 December 2017; Accepted 6 February 2018; Published 26 March 2018

Academic Editor: Simone Cinquemani

Copyright © 2018 Fei Dong et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

How to Cite this Article

Fei Dong, Xiao Yu, Enjie Ding, Shoupeng Wu, Chunyang Fan, and Yanqiu Huang, “Rolling Bearing Fault Diagnosis Using Modified Neighborhood Preserving Embedding and Maximal Overlap Discrete Wavelet Packet Transform with Sensitive Features Selection,” Shock and Vibration, vol. 2018, Article ID 5063527, 29 pages, 2018. https://doi.org/10.1155/2018/5063527.