Unsupervised Feature-Preserving CycleGAN for Fault Diagnosis of Rolling Bearings Using Unbalanced Infrared Thermal Imaging Sample

• Main Authors: Guo, Lujiale, Chuah, Joon Huang, Raymond, Wong Jee Keen, Gu, Xiaohui, Yao, Jie, Chang, Xiangqian
• Format: Article
• Published: Institute of Electrical and Electronics Engineers 2024
• Subjects: TK Electrical engineering. Electronics Nuclear engineering
• Online Access: http://eprints.um.edu.my/45856/; https://doi.org/10.1109/ACCESS.2024.3365551

The fault diagnosis of rolling bearing is of great significance in industrial safety. The method of infrared thermal image combined with neural network can diagnose the fault of rolling bearing in a non-contact manner, however its data in different scenes are often unbalanced and difficult to obtain...