… other data augmentation algorithms can solve the problem of … To deal with data augmentation
under large speed fluctuation… of the original sample for data augmentation. The DAESPN …

… diagnostic performance of the deep neural network is extensively evaluated with respect to
data augmentation … intelligent fault diagnosis method offers a new and promising approach. …

… In this study, a three-stage SSL approach using data augmentation (DA) and metric learning
is proposed for an intelligent bearing fault diagnosis under limited labeled data. In the first …

… of massive monitoring data, the availability of fault samples will be limited … intelligent fault
diagnosis method for planetary gearbox under extremely few samples. To settle these problems…

… Intelligent fault diagnosis based on machine learning has yielded a wealth of research results.
However, fault diagnosis … Therefore, it is necessary to research intelligent fault diagnosis …

… Abstract—Deep learning based intelligent fault detection for mechanical … sufficient fault
samples by monitoring sensors, which restricts the accuracy of existing intelligent fault diagnostic …

… into three categories: the data augmentation-based, the feature … intelligent fault diagnosis in
the small & imbalanced data … first level was restricted to intelligent fault diagnosis. For S&I-IFD…

… other research fields, of which is less discussed in fault diagnosis. … data augmentation
method for fault diagnosis is proposed in this work to address the problem of insufficient fault data. …

… A problem in data-driven fault diagnosis of civil aviation hydraulic … problem, this paper
develops a data augmentation method, namely empirical mode reconstruction (EMR), to augment …

… However, this study used an intelligent fault diagnosis method based on … data augmentation
methods on the experiment. The information of the datasets used to verify data augmented …