Temporal Local Correntropy Representation for Fault Diagnosis of Machines | IEEE Journals & Magazine | IEEE Xplore
Scheduled Maintenance: On Monday, 27 January, the IEEE Xplore Author Profile management portal will undergo scheduled maintenance from 9:00-11:00 AM ET (1400-1600 UTC). During this time, access to the portal will be unavailable. We apologize for any inconvenience.

Temporal Local Correntropy Representation for Fault Diagnosis of Machines


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 More

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)
Page(s): 11868 - 11877
Date of Publication: 06 March 2023

ISSN Information:

Funding Agency:


References

References is not available for this document.