A Series DC Arc Fault Detection Method Based on Steady Pattern of High-Frequency Electromagnetic Radiation

作者：Shuangle Zhao, Yao Wang, Feng Niu, Chen Zhu, Youxin Xu, Kui Li · 发表于：IEEE Transactions on Plasma Science · 年份：2019 · DOI：10.1109/tps.2019.2932747 · 被引用次数：56 · 研究领域：Electrical Fault Detection and Protection、Integrated Circuits and Semiconductor Failure Analysis、Risk and Safety Analysis

Due to detection difficulties, dc arc faults are one of the most dangerous risks in dc power systems. Most traditional studies are based on arc current, which may change during normal operation and cause unwanted trips. Another problem with the traditional methods is that the detection threshold may need to be adjusted for different photovoltaic (PV) systems; otherwise, it will cause malfunctions. To solve the aforementioned problems, a series arc fault detection method based on steady patterns of the frequency domain is proposed. The proposed method utilizes the electromagnetic radiation (EMR) emitted by an arc as a testing basis, avoiding the occurrence of unwanted trips. Patterns such as the structural similarity index (SSIM) and 6-dB bandwidth bins (6-dB BWBs) are calculated to extract the similarity of the steady-burning arc spectra. The experimental verification shows that the proposed steady-pattern-based method can accurately identify arc faults in different dc power systems, discriminate arc faults from normal operations, effectively avoid the occurrence of malfunctions, and can be used as a supplementary technique to traditional methods.