A Probabilistic Bayesian Parallel Deep Learning Framework for Wind Turbine Bearing Fault Diagnosis

A Probabilistic Bayesian Parallel Deep Learning Framework for Wind Turbine Bearing Fault Diagnosis

The technology of fault diagnosis helps improve the reliability of wind turbines. Difficulties in feature extraction and low confidence in diagnostic results are widespread in the process of deep learning-based fault diagnosis of wind turbine bearings. Therefore, a probabilistic Bayesian parallel de...

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Bibliographic Details
Main Authors: Liang Meng, Yuanhao Su, Xiaojia Kong, Xiaosheng Lan, Yunfeng Li, Tongle Xu, Jinying Ma
Format: Article
Language:English
Published: MDPI AG 2022-10-01
Series:Sensors
Subjects:
wind turbine bearing
fault diagnosis
uncertainty
BayesianPDL
Online Access:https://www.mdpi.com/1424-8220/22/19/7644

Internet

https://www.mdpi.com/1424-8220/22/19/7644

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