Dynamics Modeling of Bearing with Defect in Modelica and Application in Direct Transfer Learning from Simulation to Test Bench for Bearing Fault Diagnosis

Dynamics Modeling of Bearing with Defect in Modelica and Application in Direct Transfer Learning from Simulation to Test Bench for Bearing Fault Diagnosis

In data-driven bearing fault diagnosis, sufficient fault data are fundamental for algorithm training and validation. However, only very few fault measurements can be provided in most industrial applications, bringing the dynamics model to produce bearing response under defects. This paper built a Mo...

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Bibliographic Details
Main Authors: Diwang Ruan, Yuxiang Chen, Clemens Gühmann, Jianping Yan, Zhirou Li
Format: Article
Language:English
Published: MDPI AG 2022-02-01
Series:Electronics
Subjects:
bearing
transfer learning
dynamics model
fault diagnosis
modelica
Convolutional Neural Network (CNN)
Online Access:https://www.mdpi.com/2079-9292/11/4/622

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https://www.mdpi.com/2079-9292/11/4/622

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