Output details
15 - General Engineering
University of Sheffield
Article title
Recognition of ultra high frequency partial discharge signals using multi-scale features
Type
D - Journal article
Title of journal
IEEE Transactions on Dielectrics and Electrical Insulation
Article number
-
Volume number
19
Issue number
4
First page of article
1412
ISSN of journal
10709878
Year of publication
2012
URL
-
Number of additional authors
3
Additional information
Harrison was selected by the State Key Laboratory in High Voltage at ChongQing University (CQU) as one of 10 international experts to collaborate on this multinational project (China, USA, UK) within the Chinese Government $88M “111 Project” (Prof M Chen). This paper has contributed to the award of follow-on funding (RMB960k p.a. to 2018) to CQU. A reduced complexity solution for incipient fault detection in HV transformers, suited to implementation on a modest hand-held device, was found by exploiting data structure, yielding equal performance to class-leaders, but with greatly reduced computational requirements and improved robustness.
Interdisciplinary
-
Cross-referral requested
-
Research group
None
Proposed double-weighted
No
Double-weighted statement
-
Reserve for a double-weighted output
No
Non-English
No
English abstract
-
