Abstract:
In view of the good correlation measurement ability of correntropy, in this article, we propose a temporal local correntropy representation (TLCE) method based on the loc...Show MoreMetadata
Abstract:
In view of the good correlation measurement ability of correntropy, in this article, we propose a temporal local correntropy representation (TLCE) method based on the local correntropy matrix for fault diagnosis of machines. In TLCE, a sample is divided into several segments, and then, the correlation between these segments is expressed by correntropy. Finally, the correntropy matrix composed of the correntropy is regarded as the feature of each sample. The proposed TLCE model is validated by experiments of three bearing datasets and one gear dataset. And results demonstrate that compared with other methods, TLCE has obvious advantages, such as effectiveness and robustness.
Published in: IEEE Transactions on Industrial Informatics ( Volume: 19, Issue: 12, December 2023)