Cross-domain fault diagnosis method for rolling bearings based on contrastive universal domain adaptation

Shouqiang Kang; Xi Tang; Yujing Wang; Qingyan Wang; Jinbao Xie

doi:10.1016/j.isatra.2023.12.019

ScienceGate Book Chapters

JOURNAL ARTICLE

Cross-domain fault diagnosis method for rolling bearings based on contrastive universal domain adaptation

Shouqiang Kang Xi Tang Yujing Wang Qingyan Wang Jinbao Xie

Year: 2023 Journal: ISA Transactions Vol: 146 Pages: 195-207 Publisher: Elsevier BV

DOI: 10.1016/j.isatra.2023.12.019

Get Full-Text PDF Get Analytical Report

Keywords:

Weighting Computer science Fault (geology) Artificial intelligence Domain (mathematical analysis) Pattern recognition (psychology) Feature (linguistics) Domain adaptation Class (philosophy) Bearing (navigation) Data mining Entropy (arrow of time) Adaptation (eye) Mathematics Classifier (UML)

Metrics

Cited By

7.41

FWCI (Field Weighted Citation Impact)

Refs

0.97

Citation Normalized Percentile

Is in top 1%

Is in top 10%

Citation History

Topics

Domain Adaptation and Few-Shot Learning

Physical Sciences → Computer Science → Artificial Intelligence

Machine Fault Diagnosis Techniques

Physical Sciences → Engineering → Control and Systems Engineering

Cross-domain fault diagnosis method for rolling bearings based on contrastive universal domain adaptation

Metrics

Citation History

Topics

Related Documents

Unsupervised fault diagnosis method for rolling bearings based on federated universal domain adaptation

Online Domain Adaptation for Rolling Bearings Fault Diagnosis with Imbalanced Cross-Domain Data

Cross-Domain Fault Diagnosis of Rolling Bearings Using Domain Adaptation with Classifier Discrepancy

Self-supervised learning-based dual-classifier domain adaptation model for rolling bearings cross-domain fault diagnosis

Adversarial domain adaptation based on contrastive learning for bearings fault diagnosis