… In recent years, deep learning models have been extensively implemented in … fault detection
and diagnosis (FDD) systems. The deep architecture’s automated feature learning process …

… to ANNs and Deep Learning, also … Deep Learning to fault detection in wind turbines.
Finally, we discuss the reviewed articles with regard to perspectives for applying Deep Learning …

… The fault detection of automotive instrument cluster systems in … detection of faults. We present
a novel approach for automated Fault Detection and Isolation (FDI) based on deep learning…

… However, fault features are often weakened and disturbed by the time-varying harmonics …
for early fault detection under time-varying conditions. In this study, a deep learning model is …

… A novel data-driven deep-learning system for large-scale wind turbine … to learn successfully
from the actions of human diagnostic experts and provide early and robust fault detection on …

… [43] presented a general framework common to all the process monitoring fault detection (PMFD)
and discussed the future challenges of this research. Ge et al. [2] provided a review …

… fault detection workflow using both CNN and directional smoothing/sharpening. Applying both
on a realistic synthetic fault … that the proposed fault detection workflow can perform well on …

… , deep learning for fault diagnosis is put forward in this paper. It is a real time online scheme
that can enhance the accuracy of detection… The average fault detection rates on our test data …

… to detect and diagnose machinery bearing fault and is accepted as a … fault detection and
diagnosis employing deep learning … fault detection and diagnosis using the CWRU dataset. …

… We formulate the seismic fault detection problem as an image classification task, which takes
as input the seismic image patches around a certain central point in the seismic image cube…