A Multi-Source Domain Adaptation Method for Bearing Fault Diagnosis with Dynamically Similarity Guidance on Incomplete Data

A Multi-Source Domain Adaptation Method for Bearing Fault Diagnosis with Dynamically Similarity Guidance on Incomplete Data

In actual industrial scenarios, collecting a complete dataset with all fault categories under the same conditions is challenging, leading to a loss in fault category knowledge in single-source domains. Deep learning domain adaptation methods face difficulties in multi-source scenarios due to insuffi...

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Bibliographic Details
Main Authors: Juan Tian, Shun Zhang, Gang Xie, Hui Shi
Format: Article
Language:English
Published: MDPI AG 2025-01-01
Series:Actuators
Subjects:
multi-source domain adaptation
fault diagnosis
dynamic similarity measure
incomplete data
rotating machine
Online Access:https://www.mdpi.com/2076-0825/14/1/24
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