A Series Arc Fault Detection Strategy for Single-Phase Boost PFC Rectifiers

Abstract

This paper proposes a series arc fault detection algorithm which incorporates peak voltage and harmonic current detectors for single-phase boost power factor correction (PFC) rectifiers. The series arc fault model is also proposed to analyze the phenomenon of the arc fault and detection algorithm. For arc detection, the virtual dq transformation is utilized to detect the peak input voltage. In addition, multiple combinations of low-and high-pass filters are applied to extract the specific harmonic components which show the characteristics of the series arc fault conditions. The proposed model and the arc detection method are experimentally verified through a boost PFC rectifier prototype operating under the grid-tied condition with an artificial arc generator manufactured under the guidelines for the Underwriters Laboratories (UL) 1699 standard.

A Novel Algorithm for Fast DC Electric Arc Detection

“…Various tests have been conducted to select the most efficient algorithm and descriptor for the detection of arcs in household mains [48][49][50][51][52] and photovoltaic installations [53][54][55][56][57]. For both AC and DC systems, among others, the following signal processing algorithms have been taken into consideration: Wavelet transform and Fast Fourier Transform (FFT) [1,[3][4][5]28,29,58,59]; Short-Time Fourier Transform (STFT) [38,42,48]; Finite Impulse Response (FIR) filtration and derivative [51,[60][61][62]; Wigner-Ville Distribution (WVD) [11]; Signal-to-Noise Ratio (SNR) [27]; statistics [26]; and mathematical morphology [30]. Neural networks/machine learning have been used to extract the arc features [12][13][14][15]41,49,63], as well as image processing algorithms [64,65].…”

A Novel Arc Fault Detector for Early Detection of Electrical Fires

“…A Kalman filtering algorithm, artificial neural networks and fuzzy logic algorithms have been separately used to classify arc faults and normal states [ 40 , 41 , 42 ]. The harmonic components of arc fault currents have been analyzed [ 43 , 44 ]. The reconstructed information entropy of each current frequency band has been calculated to obtain the feature frequency bands of arc faults [ 45 ].…”