A New Fault Diagnosis Method for Unbalanced Data Based on 1DCNN and L2-SVM

A New Fault Diagnosis Method for Unbalanced Data Based on 1DCNN and L2-SVM

In general, the measured health condition data from rolling bearings usually exhibit imbalanced distribution. However, traditional intelligent fault diagnosis methods usually assume that the data categories are balanced. To improve the diagnosis accuracy of unbalanced datasets, a new fault diagnosis...

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Bibliographic Details
Main Authors: Baoquan Hu, Jun Liu, Rongzhen Zhao, Yue Xu, Tianlong Huo
Format: Article
Language:English
Published: MDPI AG 2022-09-01
Series:Applied Sciences
Subjects:
bearing
convolutional neural network
deep learning
fault diagnosis
unbalanced data
Online Access:https://www.mdpi.com/2076-3417/12/19/9880

Internet

https://www.mdpi.com/2076-3417/12/19/9880

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