Abstract Series arc fault is one of the main causes of electric fire. Effective detection of series arc fault is of great significance in preventing electric fire. The series arc fault experiment of multi-load circuit was carried out with six kinds of household loads. A new arc fault detection and line selection method was proposed. Firstly, fractional Fourier transform of main loop current signal was used to construct an arc fault image matrix. The matrix can fully reflect the change process of current signal from time domain to frequency domain. Secondly, the local binary pattern (LBP) was used to describe the local texture features of the image matrix. And the gray distribution histogram of the LBP image was obtained statistically. The LBP histogram data under different experimental conditions were used to establish a database. Finally, the maximum correlation coefficient matching criterion was used to realize arc fault detection and line selection. The test results show that the proposed method can realize arc fault detection and line selection in multi-load circuit, and the accuracy of detection and line selection is higher than 90%.
Guo Fengyi,Gao Hongxin,Tang Aixia等. Series Arc Fault Detection and Line Selection Based on Local Binary Pattern Histogram Matching[J]. Transactions of China Electrotechnical Society, 2020, 35(8): 1653-1661.
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2020, Vol. 35 
