Series Arc Fault Identification Method in Aviation Lines Based on Multi-Information Fusion
Cui Ruihua1, 2, Wang Yang1, 2, Wang Chuanyu1, 2, Li Yingnan1, 2, Li Fengfeng1, 2
1. State Key Laboratory of Reliability and Intelligence of Electrical Equipment Hebei University of Technology Tianjin 300130 China; 2. Key Laboratory of Electromagnetic Field and Electrical Apparatus Reliability of Hebei Province Hebei University of Technology Tianjin 300130 China
Abstract：The working environment of aeronautical circuit is complicated and the reliability of arc fault discrimination is relatively high. However, the single feature identification method has relatively poor diagnostic efficiency. To solve this problem, a multi-feature information fusion algorithm for the detection of arc faults in aviation low voltage distribution lines is proposed. The characteristics of the line current time domain, frequency domain and time-frequency domain were extracted by using the four feature quantities of pulse width percentage, coefficient of variation, inter-harmonic mean and wavelet singular entropy. They were taken for information fusion by establishing the evaluation model of arc fault based on mutation principle to obtain arc fault evaluation index, and the arc fault is judged according to the evaluation index. The results show that the evaluation criteria under normal conditions and arc faults are distinct and easy to set thresholds, and this method is applicable to multiple load types and current levels.
崔芮华, 王洋, 王传宇, 李英男, 李锋锋. 基于多信息融合的航空线路串联故障电弧识别方法[J]. 电工技术学报, 2019, 34(zk1): 118-125.
Cui Ruihua, Wang Yang, Wang Chuanyu, Li Yingnan, Li Fengfeng. Series Arc Fault Identification Method in Aviation Lines Based on Multi-Information Fusion. Transactions of China Electrotechnical Society, 2019, 34(zk1): 118-125.
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2019, Vol. 34 
