Arc fault detection method based on voltage characteristic energy amplitude and phase mapping distribution distances

The existing series arc fault detection methods are mainly realized by characteristics of current, due to the diversity of load current waveforms, it is difficult to construct universal detection criteria for this type of methods. In case of arc fault, the existence of power supply and line inductance causes the fault information of characteristic frequency band of arc voltage source at the fault point to be reflected at the monitoring point, which provides a new idea for arc fault detection. Based on the analysis of the characteristic law of the arc voltage at the fault point and the fault voltage at the monitoring point, the selection of the characteristic frequency band of the fault information is demonstrated. Based on the distribution characteristics of high-frequency signals of arc voltage waveforms with different loads, a detection strategy for classifying loads into switching power supply and non-switching power supply is proposed. According to their respective fault characteristics, fault detection methods based on voltage characteristic energy amplitude and phase mapping distribution distance are proposed, which construct the comprehensive detection strategy using the amplitude and phase information of characteristic energy to meet the fault detection for different load types. Experimental results show that this method can realize fault detection with different line parameters and load types.