TY - JOUR
T1 - Detecting Series Arc Faults Using High-Frequency Components of Branch Voltage Coupling Signal
AU - He, Zhipeng
AU - Xu, Zixiao
AU - Zhao, Hu
AU - Li, Weilin
AU - Zhen, Yan
AU - Ning, Wenjun
N1 - Publisher Copyright:
© 1963-2012 IEEE.
PY - 2024
Y1 - 2024
N2 - Series arc faults (SAFs) are important safety issues in low-voltage ac distribution networks. However, the load type and circuit topology are increasing, and arcing current features are easily affected by these factors, which makes SAF detection very challenging. This article proposes a new method for detecting SAFs in real scenarios containing multiple load types and complex circuit topologies. The proposed method uses the branch voltage coupling signal (BVCS) as the detection signal. First, the wavelet transform is employed to preprocess the BVCS to simplify the representation of fault components. Second, the absolute value sum of wavelet transform detail coefficients (AVSDCs) is utilized to characterize them. Then, the complete detection algorithm is designed based on the difference of AVSDC between normal conditions and arc faults and the continuity of SAFs. Finally, an online arc fault detection device (AFDD) is developed to validate the accuracy of the proposed method and its generalization ability. The results show that the proposed method has good detection accuracy under complex working conditions with multiple load types and circuit topologies.
AB - Series arc faults (SAFs) are important safety issues in low-voltage ac distribution networks. However, the load type and circuit topology are increasing, and arcing current features are easily affected by these factors, which makes SAF detection very challenging. This article proposes a new method for detecting SAFs in real scenarios containing multiple load types and complex circuit topologies. The proposed method uses the branch voltage coupling signal (BVCS) as the detection signal. First, the wavelet transform is employed to preprocess the BVCS to simplify the representation of fault components. Second, the absolute value sum of wavelet transform detail coefficients (AVSDCs) is utilized to characterize them. Then, the complete detection algorithm is designed based on the difference of AVSDC between normal conditions and arc faults and the continuity of SAFs. Finally, an online arc fault detection device (AFDD) is developed to validate the accuracy of the proposed method and its generalization ability. The results show that the proposed method has good detection accuracy under complex working conditions with multiple load types and circuit topologies.
KW - Arc fault detection device (AFDD)
KW - branch voltage coupling signal (BVCS)
KW - fault detection
KW - pulse spike
KW - series arc fault (SAF)
UR - http://www.scopus.com/inward/record.url?scp=85202746325&partnerID=8YFLogxK
U2 - 10.1109/TIM.2024.3449954
DO - 10.1109/TIM.2024.3449954
M3 - 文章
AN - SCOPUS:85202746325
SN - 0018-9456
VL - 73
JO - IEEE Transactions on Instrumentation and Measurement
JF - IEEE Transactions on Instrumentation and Measurement
M1 - 3528413
ER -