Identification of Series Arc Fault Occurred in the Three-Phase Motor With Frequency Converter Load Circuit via VMD and Entropy-Based Features

Series arc fault (SAF) is the main cause of the electrical fire and other safety accidents. In the industrial field, now, it is still a lack of effective solutions to accurately identify the SAF that occurred in the three-phase motor with the frequency converter load (TPMFCL) circuit. The transient SAF experiments and two-phase SAF experiments in the TPMFCL circuit were carried out. A novel SAF identification method based on variational mode decomposition (VMD) of a single-phase current signal and entropy-based features was proposed. First, the current signal is decomposed by VMD. The intrinsic mode function (IMF) components whose central frequency is within the frequency band between 0 and 650 Hz are obtained. Second, the sample entropy and the energy entropy of those IMFs are calculated and used as the fault features. Finally, the SAF is identified by using a support vector machine optimized by firefly algorithm (FA-SVM). Both the identification accuracy and calculation time of the method were systematically tested by changing several different test conditions. When the sampling frequency is 2 kHz and the sample length is four current cycles, the method can accurately and quickly identify the SAF that occurred in the TPMFCL circuit even under complicated harmonic power supply conditions. The conclusions can be applied to develop the industrial arc fault circuit interrupter (AFCI) used in the TPMFCL circuit.