LAPSE:2023.28974
Published Article

LAPSE:2023.28974
A Novel Algorithm for Fast DC Electric Arc Detection
April 12, 2023
Abstract
Electric arcing is a common problem in DC power systems. To overcome this problem, the electric arc detection algorithm has been developed as a faster alternative to existing algorithms. The following issues are addressed in this paper: The calculation of the proposed algorithm of incremental decomposition of the signal over time; the computational complexity of Fast Fourier Transform (FFT) and the incremental decomposition; the test bench used to measure electric arcs at given parameters; the analysis of measurements using FFT; and the analysis of measurements using incremental decomposition. The parameters are the DC voltage, electric load, and width of the gap between electrodes. The results showed that the proposed algorithm allows for a faster calculation—about seven times faster than FFT—and cheaper implementation in electric arc detection devices than FFT.
Electric arcing is a common problem in DC power systems. To overcome this problem, the electric arc detection algorithm has been developed as a faster alternative to existing algorithms. The following issues are addressed in this paper: The calculation of the proposed algorithm of incremental decomposition of the signal over time; the computational complexity of Fast Fourier Transform (FFT) and the incremental decomposition; the test bench used to measure electric arcs at given parameters; the analysis of measurements using FFT; and the analysis of measurements using incremental decomposition. The parameters are the DC voltage, electric load, and width of the gap between electrodes. The results showed that the proposed algorithm allows for a faster calculation—about seven times faster than FFT—and cheaper implementation in electric arc detection devices than FFT.
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Keywords
electric arc, FFT, incremental decomposition, signal processing
Subject
Suggested Citation
Dołęgowski M, Szmajda M. A Novel Algorithm for Fast DC Electric Arc Detection. (2023). LAPSE:2023.28974
Author Affiliations
Dołęgowski M: Faculty of Electrical Engineering, Automatic Control and Informatics, Opole University of Technology, Prószkowska 76, 45-758 Opole, Poland [ORCID]
Szmajda M: Faculty of Electrical Engineering, Automatic Control and Informatics, Opole University of Technology, Prószkowska 76, 45-758 Opole, Poland [ORCID]
Szmajda M: Faculty of Electrical Engineering, Automatic Control and Informatics, Opole University of Technology, Prószkowska 76, 45-758 Opole, Poland [ORCID]
Journal Name
Energies
Volume
14
Issue
2
Article Number
en14020288
Year
2021
Publication Date
2021-01-07
ISSN
1996-1073
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Original Submission
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PII: en14020288, Publication Type: Journal Article
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LAPSE:2023.28974
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https://doi.org/10.3390/en14020288
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