TY - GEN
T1 - Characteristics analysis and detection of AC arc fault in SSPC based on wavelet transform
AU - Zhao, Yingqun
AU - Zhang, Xiaobin
AU - Dong, Yanjun
AU - Li, Weilin
N1 - Publisher Copyright:
© 2016 IEEE.
PY - 2016/11/17
Y1 - 2016/11/17
N2 - Solid state power controller (SSPC) is the key component of advanced aircraft power distribution system and is adopted to control and protect the transmission lines intelligently. In addition to the common faults such as the overcurrent and short circuit, arc faults will also damage the transmission lines in aviation electrical system. In order to improve the overall safety of the aircraft, it is necessary to study the SSPC with function of arc fault detection (AFD). In this paper, the discharge characteristics and classification of arc faults are introduced first. Then, the research status of AC AFD methods are summarized; meanwhile, this paper analyses those methods advantages and disadvantages, and a new method for arc fault detection based on arc fault difference signal analysis and wavelet transform is proposed. For series arc characteristics described, experimental Test bed is built to obtain the data of aviation AC series arc fault under two different loads. The fundamental waves of the collected current signals are removed, then the obtained difference signal is analyzed by the stationary wavelet transform in matlab, and then the modulus maxima of a layer of detail waveform are selected as the feature for detection. The experimental results show that this method can improve the accuracy of fault arc detection.
AB - Solid state power controller (SSPC) is the key component of advanced aircraft power distribution system and is adopted to control and protect the transmission lines intelligently. In addition to the common faults such as the overcurrent and short circuit, arc faults will also damage the transmission lines in aviation electrical system. In order to improve the overall safety of the aircraft, it is necessary to study the SSPC with function of arc fault detection (AFD). In this paper, the discharge characteristics and classification of arc faults are introduced first. Then, the research status of AC AFD methods are summarized; meanwhile, this paper analyses those methods advantages and disadvantages, and a new method for arc fault detection based on arc fault difference signal analysis and wavelet transform is proposed. For series arc characteristics described, experimental Test bed is built to obtain the data of aviation AC series arc fault under two different loads. The fundamental waves of the collected current signals are removed, then the obtained difference signal is analyzed by the stationary wavelet transform in matlab, and then the modulus maxima of a layer of detail waveform are selected as the feature for detection. The experimental results show that this method can improve the accuracy of fault arc detection.
KW - AC Arc Fault Detection
KW - Difference signal
KW - Stationary Wavelet Transform
UR - https://www.scopus.com/pages/publications/85006728559
U2 - 10.1109/AUS.2016.7748097
DO - 10.1109/AUS.2016.7748097
M3 - 会议稿件
AN - SCOPUS:85006728559
T3 - AUS 2016 - 2016 IEEE/CSAA International Conference on Aircraft Utility Systems
SP - 476
EP - 481
BT - AUS 2016 - 2016 IEEE/CSAA International Conference on Aircraft Utility Systems
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 2016 IEEE/CSAA International Conference on Aircraft Utility Systems, AUS 2016
Y2 - 10 October 2016 through 12 October 2016
ER -