Bogarra Santiago, Moreno-Eguilaz Manuel, Ortega-Redondo Juan Antonio, Riba Jordi-Roger
Department of Electrical Engineering, Universitat Politècnica de Catalunya, Campus of Terrassa, 08222, Terrassa, Spain.
Department of Electronic Engineering, Universitat Politècnica de Catalunya, Campus of Terrassa, 08222, Terrassa, Spain.
Sci Data. 2024 Dec 19;11(1):1396. doi: 10.1038/s41597-024-04253-5.
This paper presents an experimental dataset developed for the detection of parallel arc faults in aircraft electrical systems. This dataset is based on a total of 960 experiments performed in a low-pressure chamber under different conditions using two electrodes placed on the surface of an insulating material. These experiments correspond to 2 insulating materials, 12 electrode distances, and 10 pressure conditions representative of aircraft environments. Each experimental condition was repeated four times, resulting in 960 experimental recordings, each containing one million samples of time, current, and voltage signals of the electric arc induced on the surface of the insulating material. The dataset can be used to model arc behavior under different pressure conditions, to identify patterns that indicate the presence of an arc, and to accelerate the improvement of arc identification. This dataset has the potential to be used to develop arc fault detection and identification methods for more electric and all-electric aircraft and other electric vehicles.
本文介绍了一个为检测飞机电气系统中的并联电弧故障而开发的实验数据集。该数据集基于在低压舱中使用放置在绝缘材料表面的两个电极在不同条件下进行的总共960次实验。这些实验对应于2种绝缘材料、12个电极距离以及代表飞机环境的10种压力条件。每个实验条件重复了4次，从而得到960个实验记录，每个记录包含绝缘材料表面感应电弧的时间、电流和电压信号的100万个样本。该数据集可用于模拟不同压力条件下的电弧行为，识别表明电弧存在的模式，并加速电弧识别的改进。这个数据集有潜力用于开发适用于更多电动和全电动飞机以及其他电动车辆的电弧故障检测和识别方法。
