A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2020; you can also visit the original URL.
The file type is application/pdf
.
Intelligent Deep Adversarial Network Fault Diagnosis Method Using Semisupervised Learning
2020
Mathematical Problems in Engineering
In recent years, deep learning has become a popular issue in the intelligent fault diagnosis of industrial equipment. Under practical working conditions, although the collected vibration data are of large capacity, most of the vibration data are not labeled. Collecting and labeling sufficient fault data for each condition are unrealistic. Therefore, constructing a reliable fault diagnosis model with a small amount of labeled vibration data is a significant problem. In this paper, the vibration
doi:10.1155/2020/8503247
fatcat:3kaizhy7ofa67onqplkywhdily