作者
Kun Yu, Tian Ran Lin, Hui Ma, Xiang Li, Xu Li
发表日期
2021
期刊
Mechanical Systems and Signal Processing
卷号
146
页码范围
107043
出版商
Academic Press
简介
Limited condition monitoring data are recorded with label information in practice, which make the fault identification task more challenging. A semi-supervised learning (SSL) approach can be employed to increase the identification performance of the classifiers under such situation. 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 stage, a DA method comprising seven DA strategies is presented to expand the feature space for the limited labeled samples under each healthy conditions. An optimization objective combining a cross entropy loss and a triplet loss is adopted to enlarge the margin between the feature distributions of limited labeled samples under different healthy conditions. In the second stage, a K-means technique is employed to acquire the cluster centers for the limited …
学术搜索中的文章
K Yu, TR Lin, H Ma, X Li, X Li - Mechanical Systems and Signal Processing, 2021