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Shock and Vibration
Volume 2015, Article ID 964805, 10 pages
Research Article

Performance Improvement of Ensemble Empirical Mode Decomposition for Roller Bearings Damage Detection

Dynamics & Identification Research Group, Department of Mechanical and Aerospace Engineering, Politecnico di Torino, Corso Duca degli Abruzzi 24, 10129 Torino, Italy

Received 10 October 2014; Revised 11 February 2015; Accepted 24 February 2015

Academic Editor: Ahmet S. Yigit

Copyright © 2015 Ali Akbar Tabrizi 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 [4 citations]

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

  • Ran Zhang, Lifeng Wu, Xiaohui Fu, and Beibei Yao, “Classification of bearing data based on deep belief networks,” 2016 Prognostics and System Health Management Conference (PHM-Chengdu), pp. 1–6, . View at Publisher · View at Google Scholar
  • Ali Akbar Tabrizi, Hussein Al-Bugharbee, Irina Trendafilova, and Luigi Garibaldi, “A cointegration-based monitoring method for rolling bearings working in time-varying operational conditions,” Meccanica, 2016. View at Publisher · View at Google Scholar
  • Zhixing Li, and Boqiang Shi, “Research of Fault Diagnosis Based on Sensitive Intrinsic Mode Function Selection of EEMD and Adaptive Stochastic Resonance,” Shock and Vibration, vol. 2016, pp. 1–12, 2016. View at Publisher · View at Google Scholar
  • Yong Lv, Jie Luo, and Cancan Yi, “Enhanced Orthogonal Matching Pursuit Algorithm and Its Application in Mechanical Equipment Fault Diagnosis,” Shock and Vibration, vol. 2017, pp. 1–13, 2017. View at Publisher · View at Google Scholar