Series DC arcing fault pose an extreme safety risk in DC power system because it is difficult to be detected.A sliding discrete fourier transform (DFT) based arcing fault recognition method is proposed to meet the requirement of real-time in detection and reduction in algorithm complexity.The arcing initiation stage is the best moment for fault detection based on analysis both in time domain and in frequency domain.Accordingly,three characteristic frequencies,40 kHz,80 kHz and 100 kHz,are selected for the point by point sliding DFT calculation.Moreover,a time-window of 200μs is used to implement the algorithm for simplicity and accuracy.Finally,it is concluded that all the three spectrums increase significantly during the arcing fault.And the sliding DFT algorithm can be applied for series DC arcing fault recognition.%在直流供电系统中,串联直流电弧故障因难于被检测而成为威胁系统安全运行的最主要因素.针对现有故障电弧识别方法运算较为复杂、实时性相对较差的不足,提出一种基于滑动离散傅里叶变换(DFT)的串联直流电弧故障识别方法.时域与频域分析表明,燃弧起始阶段是直流电弧故障识别的最佳时期,根据该阶段电弧电流的频谱特征确定滑动DFT分析频率点为40 kHz、80 kHz和100 kHz.综合考虑算法分辨率与实时性要求,采用200 μs时间窗口对电弧电流进行滑动DFT分析,并用200 us时间窗口进行滑动平均降噪处理.结果表明,发生电弧故障前后滑动DFT频谱在三个特征频率点均有明显变化,验证了滑动DFT算法用于串联直流电弧故障识别的可行性.
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