… proposed for rolling bearing fault diagnosis in this study. First, the nine data augmentation
methods are … Sun, ‘‘Intelligent rotating machinery fault diagnosis based on deep learning using …

… fruitful achievements on intelligent fault diagnosis of machines like induction motors and …
of DA-DCNN, we found that the data augmentation stage takes up most of the training time. …

… machinery fault diagnosis by improving structure of CNN and fewer parameters are needed
for training. First, the normalized fault … We validate the necessity of data augmentation in …

… equipment, data deficiency is another trouble. Both issues impede the practical application
of data-driven fault diagnosis. So as to solve the problems, a data augmentation method …

… with a filtering mechanism is proposed for fault data augmentation in this paper. First, the
self-… Xiang, “Machinery fault diagnosis based on domain adaptation to bridge the gap between …

… Based on the above analysis, how to make use of the data distribution of a few fault data to
… effect of imbalanced fault diagnosis. This article proposes a novel data augmentation method …

… Actually, the number of machinery faults and the imbalanced ratio of imbalanced dataset …
signals for data augmentation and improve the performance of imbalanced fault diagnosis on …

… One possible solution to this problem are data augmentation techniques generating … “Intelligent
rotating machinery fault diagnosis based on deep learning using data augmentation”, J …

… The occurrence of equipment fault leads to the delay of construction period, resulting in
huge economic losses, and even serious casualties. Therefore, it is significance to find the …

… datasets for fault diagnosis. Due to the collected 1D signals of machinery different from 2D
imagines, in addition to a designed reasonable composition of data augmentation to generate …