A series fault arc detection method based on the fusion of correlation theory and zero current feature

被引：0
|
作者：
Zhao H. [1 ]
Qin H. [1 ]
Liu K. [2 ]
Zhu L. [1 ]
机构：
[1] School of Mechanical and Precision Instrument Engineering, Xi'an University of Technology, Xi'an
[2] Shenyang Fire Research Institute of MEM, Shenyang
来源：
Yi Qi Yi Biao Xue Bao/Chinese Journal of Scientific Instrument | 2020年 / 41卷 / 04期
关键词：
Correlation theory; Feature fusion; Proportion coefficient of zero current time; Series fault arc detection;
D O I：
10.19650/j.cnki.cjsi.J2006019
中图分类号：
学科分类号：
摘要：
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 low-voltage single-phase 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 low-frequency 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 GB14287.4 is used in the low-voltage single-phase AC power circuit. There is no phenomenon of misjudgment and leakage. © 2020, Science Press. All right reserved.
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页码：218 / 228
页数：10
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