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Shock and Vibration
Volume 2016, Article ID 2841249, 12 pages
Research Article

Research of Fault Diagnosis Based on Sensitive Intrinsic Mode Function Selection of EEMD and Adaptive Stochastic Resonance

School of Mechanical Engineering, University of Science and Technology Beijing, Beijing 100083, China

Received 10 July 2016; Accepted 12 October 2016

Academic Editor: A. El Sinawi

Copyright © 2016 Zhixing Li and Boqiang Shi. 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.

  • Zhixing Li, and Boqiang Shi, “Extracting weak fault characteristics with adaptive singular value decomposition and stochastic resonance,” Nongye Gongcheng Xuebao/Transactions of the Chinese Society of Agricultural Engineering, vol. 33, no. 11, pp. 60–67, 2017. View at Publisher · View at Google Scholar
  • Alexander Prosvirin, Manjurul Islam, Jaeyoung Kim, and Jong-Myon Kim, “Rub-Impact Fault Diagnosis Using an Effective IMF Selection Technique in Ensemble Empirical Mode Decomposition and Hybrid Feature Models,” Sensors, vol. 18, no. 7, pp. 2040, 2018. View at Publisher · View at Google Scholar
  • Jiachen Tang, Boqiang Shi, and Zhixing Li, “Asymmetric delay feedback stochastic resonance detection method based on prior knowledge particle swarm optimization,” Chinese Journal of Physics, vol. 56, no. 5, pp. 2104–2118, 2018. View at Publisher · View at Google Scholar
  • Zhixing Li, and Boqiang Shi, “Fault Diagnosis of Rotating Machinery Based on Stochastic Resonance with a Bistable Confining Potential,” Shock and Vibration, vol. 2018, pp. 1–12, 2018. View at Publisher · View at Google Scholar