Intelligent Fault Diagnosis of Rotary Machinery by Convolutional Neural Network with Automatic Hyper-Parameters Tuning Using Bayesian Optimization

Intelligent Fault Diagnosis of Rotary Machinery by Convolutional Neural Network with Automatic Hyper-Parameters Tuning Using Bayesian Optimization

Intelligent fault diagnosis can be related to applications of machine learning theories to machine fault diagnosis. Although there is a large number of successful examples, there is a gap in the optimization of the hyper-parameters of the machine learning model, which ultimately has a major impact o...

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Bibliographic Details
Main Authors: Davor Kolar, Dragutin Lisjak, Michał Pająk, Mihael Gudlin
Format: Article
Language:English
Published: MDPI AG 2021-03-01
Series:Sensors
Subjects:
rotary machinery
fault diagnosis
convolutional neural network
classification
hyper-parameters tuning
bayesian optimization
Online Access:https://www.mdpi.com/1424-8220/21/7/2411

Internet

https://www.mdpi.com/1424-8220/21/7/2411

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