Characterization Study of AC Series Arc Faults with Different Electrode Materials in Aeronautic Applications

Arc fault characteristics are inherently highly chaotic, stochastic and are dominated by diverse factors. This paper aims to characterize the impact of different electrode materials on the performances of AC series arc faults, having as a specific reference framework the analysis and classification of such phenomena carried out in the avionic field. To this purpose, a dedicated series arc fault generation platform is constructed with reference to the aerospace standard SAE AS5692A. Then the characterization study is performed by evaluating the arc voltage and arc current signatures from the perspectives of time domain, frequency domain as well as time-frequency domain. This study provides a fundamental support to the development of a reliable arc fault detection algorithm.

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Publication Details

Published
2024-11-10
DOI
https://doi.org/10.1109/icepe-st61894.2024.10792592
Primary Topic
Electrical Fault Detection and Protection
Type
article
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article

Characterization Study of AC Series Arc Faults with Different Electrode Materials in Aeronautic Applications

Marco Faifer, Roberto Ottoboni, Youpeng Huangfu
Electrical Fault Detection and Protection
article

Characterization Study of AC Series Arc Faults with Different Electrode Materials in Aeronautic Applications

Marco Faifer, Roberto Ottoboni, Youpeng Huangfu
article en

Abstract

Arc fault characteristics are inherently highly chaotic, stochastic and are dominated by diverse factors. This paper aims to characterize the impact of different electrode materials on the performances of AC series arc faults, having as a specific reference framework the analysis and classification of such phenomena carried out in the avionic field. To this purpose, a dedicated series arc fault generation platform is constructed with reference to the aerospace standard SAE AS5692A. Then the characterization study is performed by evaluating the arc voltage and arc current signatures from the perspectives of time domain, frequency domain as well as time-frequency domain. This study provides a fundamental support to the development of a reliable arc fault detection algorithm.

Xi'an Jiaotong University (CN), Politecnico di Milano (IT)
Openalex Percentile: Top 78%
Electrical Fault Detection and Protection
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