Table of Contents Author Guidelines Submit a Manuscript
Shock and Vibration
Volume 20, Issue 2, Pages 213-225
http://dx.doi.org/10.3233/SAV-2012-00739

Rolling Element Bearing Fault Recognition Approach Based on Fuzzy Clustering Bispectrum Estimation

W.Y. Liu and J.G. Han

School of Mechanical and Electrical Engineering, Jiangsu Normal University, Xuzhou, Jiangsu, China

Received 26 June 2011; Revised 15 February 2012

Copyright © 2013 Hindawi Publishing Corporation. 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 [8 citations]

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

  • Fan Jiang, Zhencai Zhu, Wei Li, Gongbo Zhou, and Guoan Chen, “Fault identification of rotor-bearing system based on ensemble empirical mode decomposition and self-zero space projection analysis,” Journal of Sound and Vibration, 2014. View at Publisher · View at Google Scholar
  • Guangming Dong, Jin Chen, and Fagang Zhao, “A frequency-shifted bispectrum for rolling element bearing diagnosis,” Journal of Sound and Vibration, 2014. View at Publisher · View at Google Scholar
  • Kunju Shi, Shulin Liu, Hongli Zhang, and Bo Wang, “Kernel Local Linear Discriminate Method for Dimensionality Reduction and Its Application in Machinery Fault Diagnosis,” Shock and Vibration, vol. 2014, pp. 1–11, 2014. View at Publisher · View at Google Scholar
  • Chuan Li, José Valente de Oliveira, Mariela Cerrada, Fannia Pacheco, Diego Cabrera, Vinicio Sanchez, and Grover Zurita, “Observer-biased bearing condition monitoring: From fault detection to multi-fault classification,” Engineering Applications of Artificial Intelligence, vol. 50, pp. 287–301, 2016. View at Publisher · View at Google Scholar
  • Chen Lu, Yang Wang, Minvydas Ragulskis, and Yujie Cheng, “Fault diagnosis for rotating machinery: A method based on image processing,” PLoS ONE, vol. 11, no. 10, 2016. View at Publisher · View at Google Scholar
  • Guiji Tang, Xiaolong Wang, and Yuling He, “Diagnosis of compound faults of rolling bearings through adaptive maximum correlated kurtosis deconvolution,” Journal of Mechanical Science and Technology, vol. 30, no. 1, pp. 43–54, 2016. View at Publisher · View at Google Scholar
  • Lilian Shi, “Correlation Coefficient of Simplified Neutrosophic Sets for Bearing Fault Diagnosis,” Shock and Vibration, vol. 2016, pp. 1–11, 2016. View at Publisher · View at Google Scholar
  • Nourédine Yahya Bey, “Extraction of Buried Multidimensional Signals and Images in Mixed Sources of Noise,” Signal Processing, 2017. View at Publisher · View at Google Scholar