A fault mechanism-based model for bearing fault diagnosis under non-stationary conditions without target condition samples-Reference-Cited by-同舟云学术

A fault mechanism-based model for bearing fault diagnosis under non-stationary conditions without target condition samples

Published:2022-08 Issue: Volume:199 Page:111499
ISSN:0263-2241
Container-title:Measurement
language:en
Short-container-title:Measurement

Author:

Sun Hongchun,Gao Sheng,Ma Sihan,Lin Senmiao

Publisher

Elsevier BV

Subject

Applied Mathematics,Electrical and Electronic Engineering,Condensed Matter Physics,Instrumentation

Reference28 articles.

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3. Y.J. Li, B.H. Qiu, M.H. Wei, W.Q.S. Sun,X.L. Liu.Deep Learning based End-to-End Rolling Bearing Fault Diagnosis, 2019 Prognostics and System Health Management Conference (Phm-Qingdao) (2019). doi:/10.1109/PHM-Qingdao46334.2019.8942956.

4. An unsupervised bearing fault diagnosis based on deep subdomain adaptation under noise and variable load condition;Ghorvei;Meas. Sci. Technol.,2022

5. Adversarial domain adaptation of asymmetric mapping with CORAL alignment for intelligent fault diagnosis;Li;Meas. Sci. Technol.,2022

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