Entropy-based feature extraction for electromagnetic discharges classification in high-voltage power generation
Mitiche, Imene and Morison, Gordon and Nesbitt, Alan and Stewart, Brian G. and Boreham, Philip (2018) Entropy-based feature extraction for electromagnetic discharges classification in high-voltage power generation. Entropy, 20 (8). 549. ISSN 1099-4300 (https://doi.org/10.3390/e20080549)
Preview |
Text.
Filename: Mitiche_etal_Entropy2018_Entropy_based_feature_extraction_for_electromagnetic_discharges.pdf
Final Published Version License: Download (2MB)| Preview |
Abstract
This work exploits four entropy measures known as Sample, Permutation, Weighted Permutation, and Dispersion Entropy to extract relevant information from Electromagnetic Interference (EMI) discharge signals that are useful in fault diagnosis of High-Voltage (HV) equipment. Multi-class classification algorithms are used to classify or distinguish between various discharge sources such as Partial Discharges (PD), Exciter, Arcing, micro Sparking and Random Noise. The signals were measured and recorded on different sites followed by EMI expert’s data analysis in order to identify and label the discharge source type contained within the signal. The classification was performed both within each site and across all sites. The system performs well for both cases with extremely high classification accuracy within site. This work demonstrates the ability to extract relevant entropy-based features from EMI discharge sources from time-resolved signals requiring minimal computation making the system ideal for a potential application to online condition monitoring based on EMI.
-
-
Item type: Article ID code: 64875 Dates: DateEvent25 July 2018Published20 July 2018AcceptedSubjects: Technology > Electrical engineering. Electronics Nuclear engineering Department: Faculty of Engineering > Electronic and Electrical Engineering Depositing user: Pure Administrator Date deposited: 26 Jul 2018 12:31 Last modified: 25 Sep 2024 00:40 Related URLs: URI: https://strathprints.strath.ac.uk/id/eprint/64875