Zhao Huaijun1, Qin Haiyan1, Liu Kai2, Zhu Lingjian1
(1.School of Mechanical and Precision Instrument Engineering, Xi′an University of Technology, Xi′an 710048, China; 2.Shenyang Fire Research Institute of MEM, Shenyang 110034, China) 在期刊界中查找 在百度中查找 在本站中查找
Abstract:Due to the concealment and randomness of the series fault arc, it is difficult to detect these faults accurately. The relatively small current amplitude is easy to be annihilated by the load current, and the load is highly correlated with the nature of the load. To solve these problems, a method based on the lowvoltage singlephase AC series fault arc experiment platform is proposed, which refers to the UL1699 standard. Two periodic currents of the electrical circuit are collected. The proportion coefficient of zero current time and the maximum correlation coefficient of the normalized absolute value after filtering the lowfrequency components are calculated. Then, two coefficients are fused by a fuzzy logic processor to obtain the comprehensive characteristic identification coefficient of the series fault arc. It is possible to identify whether there is occurrence of series fault arc by comparing the deep combination of the achieved coefficient and the proportion coefficient of zero current time with the empirical threshold value. Experimental results show that this method can recognize up to 100% of the series fault arc when the recommended load in GB142874 is used in the lowvoltage singlephase AC power circuit. There is no phenomenon of misjudgment and leakage.