… equipment, the amount of data that can be collected for normal … , a fault diagnosis approach
for data augmentation based on PVAEGAN is proposed. The model is trained using the data …

… In real industries, conducting experiments on different types of bearings in each kind of
equipment to obtain prior knowledge for fault diagnosis that can be used for TL is uneconomical. …

… the generated data to re-implement the fault diagnosis, so as to further verify the effectiveness
of the CAN algorithm. We assess the performance of pipeline fault diagnosis according to …

… and solved the data imbalance of rotating machinery datasets… fault sample set and improved
the accuracy of fault diagnosis… J 2020 Data augmentation for bearing fault detection with a …

… of the abnormal anomaly detection model. In addition, … data to Mel-spectrogram images,
thereby achieving better performance in the fault diagnosis system to which data augmentation …

… INTRODUCTION Equipment health management is an efficient solution … equipment operators
from hazards due to equipment failure [1]. A crucial aspect of this process is fault diagnosis, …

… Furthermore, specifically for vibration signal-based machine fault diagnosis, we develop a
novel data augmentation approach to deal with length imbalance problem of vibration signals …

… , can minimize the frequency of equipment failure, but are becoming less capable of meeting
… data, unsupervised learning approaches are the most common avenue for fault detection to …

… on sensors collocated in the machines. Therefore, the possibility … data processing methods
and a data augmentation method that allow microphone arrays to be used as a fault detection …

… is of great significance to the stable operation of rotating machinery systems. However, the
… Based on the data augmentation method, CNN is added as a classifier for fault diagnosis. …