电弧
弧(几何)
电弧故障断路器
计算机科学
形式主义(音乐)
断层(地质)
算法
电气工程
工程类
电压
机械工程
地质学
地震学
物理
艺术
音乐剧
电极
量子力学
视觉艺术
短路
作者
Alexis Chabert,Patrick Schweitzer,Serge Weber,Jonathan Andrea
标识
DOI:10.1109/taes.2021.3118962
摘要
Arcing faults are a major problem in the electrical networks of aircraft. Installing a protection system, activated when a fault is detected, is one of the most effective solutions for avoiding the fires and accidents that they cause. Thanks to recent advances in artificial intelligence (AI), we can now envisage the development of reliable detectors that meet aeronautical specifications. However, in order to train an AI unit, it is necessary to create a large database of arc signals. This article proposes a method for generating thousands of arc signals, using the state-space representation formalism, according to Andrea's arc model. We will show how it is possible to simulate arc-fault signals by using the studies of two cases of arc faults. We will compare the results of the simulations with experimental measurements in order to demonstrate that the arc signals obtained are identical to those of the experiment with root-mean-square deviation errors of 0.048 V and 0.005 A.
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