Fault Diagnosis Method for Rolling Bearings Based on Two-Channel CNN under Unbalanced Datasets

Fault Diagnosis Method for Rolling Bearings Based on Two-Channel CNN under Unbalanced Datasets

As a critical component in industrial systems, timely and accurate fault diagnosis of rolling bearings is closely related to reliability and safety. Since the equipment usually operates in normal conditions with few fault samples, unbalanced data distribution problems lead to poor fault diagnosis ab...

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Bibliographic Details
Main Authors: Yufeng Qin, Xianjun Shi
Format: Article
Language:English
Published: MDPI AG 2022-08-01
Series:Applied Sciences
Subjects:
convolutional neural network
fault diagnosis
generalized S-transform
fast Fourier transform
rolling bearing
feature extraction
Online Access:https://www.mdpi.com/2076-3417/12/17/8474

Internet

https://www.mdpi.com/2076-3417/12/17/8474

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