An unsupervised fault diagnosis method for rolling bearing using STFT and generative neural networks

• Published in: Journal of the Franklin Institute Vol. 357; no. 11; pp. 7286 - 7307
• Main Authors: Tao, Hongfeng, Wang, Peng, Chen, Yiyang, Stojanovic, Vladimir, Yang, Huizhong
• Format: Journal Article
• Language: English
• Published: Elmsford Elsevier Ltd 01.07.2020; Elsevier Science Ltd
• Subjects: Deep learning; Fault diagnosis; Fourier transforms; Machine learning; Neural networks; Roller bearings; Rotating machinery; Studies

In recent years, the technique of machine learning or deep learning has been employed in intelligent fault diagnosis methods to achieve much success using massive labeled data. However, it is generally difficult or expensive to label the monitoring data in practical engineering due to its complex wo...