A fault feature extraction algorithm based on CEEMD-TVD-MOMEDA

Rolling bearings are indispensable key components in mechanical equipment, and they are also one of the most easily damaged components. To solve the problem of bearing fault feature extraction under strong noise interference, a combination of complementary ensemble average empirical mode decomposit...

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Auteurs principaux:	Jingzong Yang, Tianqing Yang, Chunchao Shi
Format:	Artigo
Langue:	Inglês
Publié:	Tamkang University Press 2021-11-01
Collection:	Journal of Applied Science and Engineering
Sujets:	complementary ensemble average empirical mode decomposition (ceemd) total variation denoising (tvd) multipoint optimal minimum entropy deconvolution adjusted fault feature extraction
Accès en ligne:	http://jase.tku.edu.tw/articles/jase-202202-25-1-0008
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