Unsupervised cross-domain rolling bearing fault diagnosis based on time-frequency information fusion

• Published in: Journal of the Franklin Institute Vol. 360; no. 2; pp. 1454 - 1477
• Main Authors: Tao, Hongfeng, Qiu, Jier, Chen, Yiyang, Stojanovic, Vladimir, Cheng, Long
• Format: Journal Article
• Language: English
• Published: Elsevier Inc 01.01.2023

In recent years, data-driven methods have been widely used in rolling bearing fault diagnosis with great success, which mainly relies on the same data distribution and massive labeled data. However, bearing equipment is in normal working state for most of the time and operates under variable operati...