Simulation of Corona Discharges and Time Domain Examination of their Emitted Electromagnetic Signals

Szirtes, Mate; Cselko, Richard

doi:10.1109/iyce45807.2019.8991576

Cited by 4 publications

(1 citation statement)

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“…The most important part of this processing is the noise filtering of the measured signals [9]- [11], because it directly affects the positioning accuracy of the measuring system. To adopt the noise filtering to the discharge phenomenon, it is necessary to perform a comprehensive examination on the characteristics of the emitted signals [12], [13]. This article presents the time-domain examination of emitted corona discharge signals and the development steps of a wavelet-transform-based novel filtering algorithm.…”

Section: Introductionmentioning

confidence: 99%

Developing a Filtering Algorithm for Partial Discharge Location Approximation Using the Emitted Electromagnetic Signals of Corona Discharges

Szirtes

Cselko

Ibáñez

2021

IEEE Trans. on Ind. Applicat.

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The aim of this article is to create a novel filtering algorithm for the emitted electromagnetic signals of corona discharges, using the special time-domain features of the continuous wavelet transform. The first part of this article therefore focuses on the time-domain examination of these signals to find characteristic features that are compatible with the wavelet transform. The second part of this article utilizes these features to create and validate the filtering algorithm. This is an important step toward creating an accurate three-dimensional partial discharge location approximation system that could contribute to preventing and finding partial-discharge-related faults. In the presented research, needle-plane corona discharge sources with different geometries are tested at both ac and dc voltages.

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Section: Introductionmentioning

confidence: 99%