Adaptive diagnosis of DC motors using R-WDCNN classifiers based on VMD-SVD
Author:
Publisher
Springer Science and Business Media LLC
Subject
Artificial Intelligence
Link
https://link.springer.com/content/pdf/10.1007/s10489-020-02087-3.pdf
Reference46 articles.
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3. Lei Y, Lin J, He Z, Zuo MJ (2013) A review on empirical mode decomposition in fault diagnosis of rotating machinery[J]. Mech Syst Signal Process 35(1–2):108–126
4. Hu A, Xiang L (2016) An optimal selection method for morphological filter’s parameters and its application in bearing fault diagnosis[J]. J Mech Sci Technol 30(3):1055–1063
5. Cheng J, Yu D, Tang J, Yang Y (2009) Application of SVM and SVD technique based on EMD to the fault diagnosis of the rotating machinery[J]. Shock Vib 16(1):89–98
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