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Shock and Vibration
Volume 2016, Article ID 9372691, 10 pages
http://dx.doi.org/10.1155/2016/9372691
Research Article

A Fault Diagnosis Scheme for Rolling Bearing Based on Particle Swarm Optimization in Variational Mode Decomposition

School of Mechanical Engineering, Wuhan University of Science and Technology, Wuhan 430081, China

Received 20 January 2016; Revised 15 May 2016; Accepted 23 May 2016

Academic Editor: Athanasios Chasalevris

Copyright © 2016 Cancan Yi 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.

Citations to this Article [17 citations]

The following is the list of published articles that have cited the current article.

  • Zhipeng Feng, Dong Zhang, and Ming Zuo, “Planetary Gearbox Fault diagnosis via Joint Amplitude and Frequency Demodulation Analysis Based on Variational Mode Decomposition,” Applied Sciences, vol. 7, no. 8, pp. 775, 2017. View at Publisher · View at Google Scholar
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  • Cancan Yi, Yong Lv, Han Xiao, Tao Huang, and Guanghui You, “Multisensor signal denoising based on matching synchrosqueezing wavelet transform for mechanical fault condition assessment,” Measurement Science and Technology, vol. 29, no. 4, pp. 045104, 2018. View at Publisher · View at Google Scholar
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  • Xian-Bo Wang, Zhi-Xin Yang, and Xiao-An Yan, “Novel Particle Swarm Optimization-Based Variational Mode Decomposition Method for the Fault Diagnosis of Complex Rotating Machinery,” IEEE/ASME Transactions on Mechatronics, vol. 23, no. 1, pp. 68–79, 2018. View at Publisher · View at Google Scholar
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  • Sinian Hu, Han Xiao, and Cancan Yi, “A Novel Detrended Fluctuation Analysis Method for Gear Fault Diagnosis Based on Variational Mode Decomposition,” Shock and Vibration, vol. 2018, pp. 1–11, 2018. View at Publisher · View at Google Scholar
  • Tatiana Chakravorti, and Pradipta Kishore Dash, “Multiclass power quality events classification using variational mode decomposition with fast reduced kernel extreme learning machine-based feature selection,” IET Science, Measurement and Technology, vol. 12, no. 1, pp. 106–117, 2018. View at Publisher · View at Google Scholar