Comparative Investigation of Corona Pulse Characteristics under DC and AC Voltages

Halil Ibrahim Uckol, Taylan Ozgur Bilgic, Suat Ilhan

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

5 Citations (Scopus)

Abstract

This paper presents a comparative investigation of AC, + DC, and - DC corona discharge pulse characteristics using machine learning (ML) algorithms. The corona discharges under different types of excitation are generated via a rod-plane elec-trode system with a constant gap spacing. The corona discharge pulses are recorded using a shunt resistor via an oscilloscope. After noise elimination from the discharge pulses, nine features extracted from the noise-free signals are inputted to several ML models to identify the corona discharges with respect to the voltage types. To increase the performance of a single model, ensemble learning, which is the combination of ML algorithms, is employed. It is observed that the corona discharge types are effectively identified with these features using ensemble learning with a high accuracy rate.

Original languageEnglish
Title of host publication2022 IEEE International Conference on High Voltage Engineering and Applications, ICHVE 2022
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9781665407502
DOIs
Publication statusPublished - 2022
Event2022 IEEE International Conference on High Voltage Engineering and Applications, ICHVE 2022 - Chongqing, China
Duration: 25 Sept 202229 Sept 2022

Publication series

Name2022 IEEE International Conference on High Voltage Engineering and Applications, ICHVE 2022

Conference

Conference2022 IEEE International Conference on High Voltage Engineering and Applications, ICHVE 2022
Country/TerritoryChina
CityChongqing
Period25/09/2229/09/22

Bibliographical note

Publisher Copyright:
© 2022 IEEE.

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