A Bearing Fault Diagnosis Method Based on Feature Selection Feedback Network and Improved D-S Evidence Fusion

A Bearing Fault Diagnosis Method Based on Feature Selection Feedback Network and Improved D-S Evidence Fusion

Bearings running state affects the normal operation of mechanical equipment. It is of great theoretical and practical value to carry out bearing fault diagnosis. In bearing fault diagnosis research, the extraction and selection of fault features can help improving the accuracy of bearing fault diagn...

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Bibliographic Details
Main Authors: Xianghong Tang, Xin Gu, Jiachen Wang, Qiang He, Fan Zhang, Jianguang Lu
Format: Article
Language:English
Published: IEEE 2020-01-01
Series:IEEE Access
Subjects:
Bearing fault diagnosis
feature selection
feedback network
D-S evidence theory
Online Access:https://ieeexplore.ieee.org/document/8964342/

Internet

https://ieeexplore.ieee.org/document/8964342/

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