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Shock and Vibration
Volume 2018, Article ID 8710190, 18 pages
Research Article

An Improved Time-Frequency Analysis Method for Instantaneous Frequency Estimation of Rolling Bearing

Department of Electrical and Electronics Engineering, Shijiazhuang Railway University, Shijiazhuang 050043, China

Correspondence should be addressed to Zengqiang Ma; moc.621@newnulqzm

Received 16 May 2018; Revised 16 August 2018; Accepted 23 August 2018; Published 18 September 2018

Academic Editor: Adam Glowacz

Copyright © 2018 Zengqiang Ma 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.

  • Yong Lv, Yi Zhang, and Cancan Yi, “Optimized Adaptive Local Iterative Filtering Algorithm Based on Permutation Entropy for Rolling Bearing Fault Diagnosis,” Entropy, vol. 20, no. 12, pp. 920, 2018. View at Publisher · View at Google Scholar
  • Siliang Lu, Ruqiang Yan, Yongbin Liu, and Qunjing Wang, “Tacholess Speed Estimation in Order Tracking: A Review With Application to Rotating Machine Fault Diagnosis,” IEEE Transactions on Instrumentation and Measurement, vol. 68, no. 7, pp. 2315–2332, 2019. View at Publisher · View at Google Scholar
  • Youfu Tang, Feng Lin, and Qian Zou, “Complexity Analysis of Time-Frequency Features for Vibration Signals of Rolling Bearings Based on Local Frequency,” Shock and Vibration, vol. 2019, pp. 1–13, 2019. View at Publisher · View at Google Scholar
  • Israel Ruiz Quinde, Jorge Chuya Sumba, Luis Escajeda Ochoa, Antonio Jr. Vallejo Guevara, and Ruben Morales-Menendez, “Bearing Fault Diagnosis Based on Optimal Time-Frequency Representation Method,” IFAC-PapersOnLine, vol. 52, no. 11, pp. 194–199, 2019. View at Publisher · View at Google Scholar