Arc fault detection data under different loads

To address the problem that the arc fault characteristics of certain loads are not significant and the line current characteristics cannot be detected effectively. In view of the wide application of a large number of nonlinear loads, it is difficult to distinguish the traditional current features from the load current features of nonlinear loads. Current features compared to those extracted from load end voltages, the latter are less affected by the load type, making the detection of faulty arcs more reliable. In this dataset, the time-domain eigenvalues of load end voltages are extracted for both single and mixed loads during the occurrence of fault arcing and normal operation. The loads are randomly combined with each other to reduce the chance.