Detection and Identification Technique for Series and Parallel DC Arc Faults

Abstract

This paper proposes a series and parallel DC arc detecting and identifying (SPADI) technique using the frequency features of the load current (<i>I_L</i>) and the load voltage (<i>V_L</i>). The frequency changes in <i>V_L</i> and <i>I_L</i> under the series and parallel arc are different. The parallel arc can only raise the high-frequency components of <i>V_L</i>. In contrast, the high-frequency components of <i>I_L</i> can be increased in both series and parallel arcs. However, the increasing frequency range is different. The high-frequency components of <i>I_L</i> generated by the series arc are concentrated in the 5 kHz to 40 kHz band. Meanwhile, the high-frequency components of <i>I_L</i> caused by the parallel arc are observed evenly in all frequency ranges. Inspired by these features, <i>V_L</i>&#x2019;s 5 kHz to 100 kHz components are used to sense the parallel arc in the proposed technique. In addition, the series arc is detected using the 5 kHz to 40 kHz and 50 kHz to 100 kHz bands of <i>I_L</i>. Experimental tests verified the proposed algorithm implemented at the digital signal processor (DSP). As a result of 160 repeated tests, the probabilities of detecting the series and parallel arc were 100 % and 96.25 %, respectively. Moreover, the probability of correctly identifying the arc type when detecting the arc was 100 %. Also, the average detection times of the series and parallel arc were 0.11 s and 0.16 s, respectively.