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JBE, vol. 26, no. 5, pp.566-574, September, 2021

DOI: https://doi.org/10.5909/JBE.2021.26.5.566

Arc Detection using Logistic Regression

Manbae Kim

C.A E-mail: manbae@kangwon.ac.kr

Abstract:

The arc is one of factors causing electrical fires. Over past decades, various researches have been carried out to detect arc occurrences. Even though frequency analysis, wavelet and statistical features have been used, arc detection performance is degraded due to diverse arc waveforms. On the contray, Deep neural network (DNN) direcly utilizes raw data without feature extraction, based on end-to-end learning. However, a disadvantage of the DNN is processing complexity, posing the difficulty of being migrated into a termnial device. To solve this, this paper proposes an arc detection method using a logistic regression that is one of simple machine learning methods.



Keyword: arc detection, logistic regression, frequency spectrum, FFT

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