Multi‐attribute quantitative bearing fault diagnosis based on convolutional neural network

Multi‐attribute quantitative bearing fault diagnosis based on convolutional neural network

Abstract Existing bearing fault diagnosis methods have some disadvantages, one being that most methods cannot completely consider all specific fault attributes. Another disadvantage is that the qualitative diagnosis method considers different fault types as a whole, and qualitative diagnosis of a si...

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Bibliographic Details
Main Authors: Shixin Zhang, Qin Lv, Shenlin Zhang, Jianhua Shan
Format: Article
Language:English
Published: Wiley 2021-12-01
Series:Cognitive Computation and Systems
Subjects:
machine bearings
feature extraction
fault diagnosis
vibrations
vibrational signal processing
convolutional neural nets
Online Access:https://doi.org/10.1049/ccs2.12016

Internet

https://doi.org/10.1049/ccs2.12016

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