Feature Extraction Method of Series Arc Fault Occurred in Three-Phase Motor With Inverter Circuit

Series arc fault is one of the main causes of electrical fire. In a three-phase motor with inverter circuit, it is difficult to accurately identify series arc fault occurred in the lines at the back of the inverter, especially when the power supply contains complicated harmonics. To solve this probl...

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Bibliographic Details
Published inIEEE transactions on power electronics Vol. 37; no. 9; pp. 11164 - 11173
Main Authors Gao, Hongxin, Wang, Zhiyong, Han, Congxin, Tang, Aixia, Guo, Fengyi, Li, Baifu
Format Journal Article
LanguageEnglish
Published New York IEEE 01.09.2022
The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
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Summary:Series arc fault is one of the main causes of electrical fire. In a three-phase motor with inverter circuit, it is difficult to accurately identify series arc fault occurred in the lines at the back of the inverter, especially when the power supply contains complicated harmonics. To solve this problem, a new feature extraction method of the series arc fault based on the current signal measured at the front of the inverter (CSMFI) was proposed. The series arc fault experiments under different harmonic power supply conditions were carried out in the three-phase motor with inverter circuit. Five-layer decomposition was performed on the CSMFI by using empirical wavelet transform. The attractor track matrix (ATM) of each decomposed signal was established. The fault features of the series arc fault were obtained by calculating and selecting the singular values of the ATM. The series arc fault was identified by using an optimized support vector machine. The effectiveness of the method and its applicability under different experimental conditions were tested. The method can simultaneously identify the series arc fault occurred in the lines at the front or back of the inverter by analyzing the CSMFI. It also has strong anti-interference ability.
ISSN:0885-8993
1941-0107
DOI:10.1109/TPEL.2022.3164246