TY - GEN
T1 - A Comprehensive Analysis of Electromagnetic Characteristics for DC Arc Fault Detection
AU - Meng, Yu
AU - Yang, Haowen
AU - Chen, Silei
AU - Hayat, Khizar
AU - Li, Xingwen
N1 - Publisher Copyright:
© 2024 IEEE.
PY - 2024
Y1 - 2024
N2 - With the development of DC power sources such as photovoltaics and energy storage, the arc fault detection and protection technology in DC distribution systems has become increasingly important. The electromagnetic characteristics are often used to construct arc fault detection features, and there are many influencing factors determining their detection effectiveness. In this paper, a DC arc fault experimental platform is established. Then, based on the electromagnetic features constructed by the synchronous compressed wavelet analysis method, the influences of antenna size, distance, direction, current level and electrode material on the electromagnetic characteristics are studied by controlling a single variable. Based on this, the advantages and disadvantages of electromagnetic signals to detect arc faults are analyzed, which provides an optimized reference for the method of detecting arc faults with electromagnetic signals. Through the autoregressive integral moving average model, the electromagnetic-based arc fault detection algorithm at a low sampling frequency in multiple scenes is obtained, and the detection accuracy is 96.13%, which is verified to have good performance.
AB - With the development of DC power sources such as photovoltaics and energy storage, the arc fault detection and protection technology in DC distribution systems has become increasingly important. The electromagnetic characteristics are often used to construct arc fault detection features, and there are many influencing factors determining their detection effectiveness. In this paper, a DC arc fault experimental platform is established. Then, based on the electromagnetic features constructed by the synchronous compressed wavelet analysis method, the influences of antenna size, distance, direction, current level and electrode material on the electromagnetic characteristics are studied by controlling a single variable. Based on this, the advantages and disadvantages of electromagnetic signals to detect arc faults are analyzed, which provides an optimized reference for the method of detecting arc faults with electromagnetic signals. Through the autoregressive integral moving average model, the electromagnetic-based arc fault detection algorithm at a low sampling frequency in multiple scenes is obtained, and the detection accuracy is 96.13%, which is verified to have good performance.
KW - electromagnetic characteristics
KW - influence factor
KW - series arc fault
KW - synchronous compressed wavelet
UR - https://www.scopus.com/pages/publications/85213362441
U2 - 10.1109/HOLM56222.2024.10768662
DO - 10.1109/HOLM56222.2024.10768662
M3 - 会议稿件
AN - SCOPUS:85213362441
T3 - Electrical Contacts, Proceedings of the Annual Holm Conference on Electrical Contacts
BT - Electrical Contacts 2024 - Proceedings of the 69th IEEE Holm Conference on Electrical Contacts, HOLM 2024
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 69th IEEE Holm Conference on Electrical Contacts, HOLM 2024
Y2 - 6 October 2024 through 10 October 2024
ER -