… of fault. This paper proposes a deep learning approach with data augmentation for rotating
machinery fault diagnosis. … with data augmentation is proposed for fault diagnosis of rotating …

… In order to validate the effectiveness of the proposed method, two multi-mode fault data
augmentation and intelligent diagnosis cases for bearings and gears are studied in this chapter. …

… synthetic data augmentation through virtual sensors for the deep learning-based fault
diagnosis of a rotating machine with 42 different classes. The original and augmented data were …

… for rotating machinery fault diagnosis, as shown in Figure 2. First, the vibration data is divided
into … Forth, we study the effect of the data augmentation methods on the experiment. The …

… other generative AI models for the data augmentation and compare with the … fault data for
different machines, only using the fault data of one machine and normal data of other machines…

… a hybrid method of data augmentation to increase the number of … our data augmentation
proposal, namely, support vector … for fault detection and classification in rotating machines. The …

… Machinery failure can cause significant financial loss as well as … , data was generated using
data augmentation techniques that are good for application to two types of time series data. …

… fault data for industrial machines. Therefore, data augmentation is a direct and effective way
to solve fault … In this paper, a novel data augmentation scheme for machine fault diagnosis …

… But in practice, the training data among each machinery health condition are unbalanced.
That is, the machine works under normal condition (NC) in most of the time, so the monitor …

… data augmentation (DA) and metric learning is proposed for an intelligent bearing fault diagnosis
under limited labeled data… on an experimental bearing fault dataset from our laboratory …