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...

Descripción completa

Guardado en:

Detalles Bibliográficos
Autores principales:	Jingzong Yang, Tianqing Yang, Chunchao Shi
Formato:	article
Lenguaje:	EN
Publicado:	Tamkang University Press 2021
Materias:	complementary ensemble average empirical mode decomposition (ceemd) total variation denoising (tvd) multipoint optimal minimum entropy deconvolution adjusted fault feature extraction Engineering (General). Civil engineering (General) TA1-2040 Chemical engineering TP155-156 Physics QC1-999
Acceso en línea:	https://doaj.org/article/fa15a986bad5459a8d6206ee871d9d29
Etiquetas:	Agregar Etiqueta Sin Etiquetas, Sea el primero en etiquetar este registro!

Sea el primero en dejar un comentario!

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

Ejemplares similares