A hybrid method combining Teager Kaiser energy operator, empirical mode decomposition and minimum entropy deconvolution for monitoring gears damages
Mechanics & Industry, 16 6 (2015) 610
Published online: 2015-09-04
Articles citing this article
The Citing articles tool gives a list of articles citing the current article.
The citing articles come from EDP Sciences database, as well as other publishers participating in CrossRef Cited-by Linking Program. You can set up your personal account to receive an email alert each time this article is cited by a new article (see the menu on the right-hand side of the abstract page).
Cited article:
This article has been cited by the following article(s):
A fully blind and adaptive filter method to solve the inverse problem in vibration-based gear damage detection
Xin Zhang, Tao Yang, Jiaxu Wang, Lei Wu, Yike Zhao, Zhiwen Liu and Tao WangStructural Health Monitoring 22 (4) 2755 (2023)
https://doi.org/10.1177/14759217221138464
A review on the application of blind deconvolution in machinery fault diagnosis
Yonghao Miao, Boyao Zhang, Jing Lin, et al.Mechanical Systems and Signal Processing 163 108202 (2022)
https://doi.org/10.1016/j.ymssp.2021.108202
Fault diagnosis on railway vehicle bearing based on fast extended singular value decomposition packet
Yan Huang, Chenguang Huang, Jianming Ding and Zechao LiuMeasurement 152 107277 (2020)
https://doi.org/10.1016/j.measurement.2019.107277
Compound Faults Feature Extraction for Rolling Bearings Based on Parallel Dual-Q-Factors and the Improved Maximum Correlated Kurtosis Deconvolution
Cui, Du, Yang, Xu and SongApplied Sciences 9 (8) 1681 (2019)
https://doi.org/10.3390/app9081681
Sparse filtering with the generalized lp / lq norm and its applications to the condition monitoring of rotating machinery
Xiaodong Jia, Ming Zhao, Yuan Di, Pin Li and Jay LeeMechanical Systems and Signal Processing 102 198 (2018)
https://doi.org/10.1016/j.ymssp.2017.09.018