Novel Series Arc Fault Detector Using High-Frequency Coupling Analysis and Multi-Indicator Algorithm

Abstract

In the field of arc fault detection, it is universally acknowledged that it is very hard to judge whether there is an arc fault through signals of the main line when a masking load (such as air compressors, lamps with dimmers, and so on) is in parallel with a resistive load, which always tends to be a fire hazard. Meanwhile, it is annoying that the normal currents of some appliances are very similar to the arcing ones. In this paper, we have found the principles of a novel detection method called high-frequency coupling, putting the neutral line (N) and the live line (L) through the current transformer (CT), which results in asymmetrical distribution of magnetic flux in the core and the only high-frequency components left in the secondary output of the CT. So it is possible for series arc fault detectors to be free from the masking loads and distinguish between the arcing and the nonarcing clearly. Thanks to this convenient method, an arc fault detector based on the microcontroller unit (MCU) has been proposed to detect arc faults effectively by means of simple multi-indicators. The experimental results show the accuracy of arc fault recognition, in all the masking tests, can reach a high level and the detector can detect an arc fault within a short time. INDEX TERMS Series arc fault, high-frequency coupling, asymmetrical distribution, magnetic flux, multi-indicators, detector, MCU, masking tests.

A Novel Differential High-Frequency Current Transformer Sensor for Series Arc Fault Detection

“…In this paper, a novel high-frequency current sensor based on the differential threading method was put forward and used in low-voltage series arc fault detection. In Reference [33], the residual magnetic flux caused by the asymmetry of the position of the live line and the neutral line was proposed as the measured physical quantity. However, the limitation of this method is that the asymmetry of the live and neutral lines is based on the fact that the secondary windings are not evenly wound around the entire core.…”

“…Although that any winding method is not perfect is a well-known fact. In Reference [33], no detailed analysis and explanation of the structure and material of the current transformer was made, but the key to this method lays in the structure of the transformer and the core material. In this paper, a non-uniform current sensor with differential threading method is proposed, which is a further improvement of the sensor used in Reference [33].…”

“…In Reference [33], no detailed analysis and explanation of the structure and material of the current transformer was made, but the key to this method lays in the structure of the transformer and the core material. In this paper, a non-uniform current sensor with differential threading method is proposed, which is a further improvement of the sensor used in Reference [33]. Through numerical analysis, the influence of the structure of the sensor and the core material on the transmission characteristics of the sensor was quantitatively studied.…”

Series Arc Fault Diagnosis and Line Selection Method Based on Recurrent Neural Network

“…Giovanni Artale obtained the characteristics of the arc fault through the Chirp Z Transform (CZT) [8]. Guanghai Bao use current transformer to extract high-frequency components and proposed an arc fault detector based on the microcontroller unit (MCU) [9]. Fengyi Guo comprehensively used wavelet packet theory, variational mode decomposition, and Wigner-Ville distri- VOLUME 4, 2016 bution to extract the time domain and time-frequency domain characteristics of arc faults, and used particle swarm optimization and grid search optimization support vector machines to establish arc fault recognition and selection model [10].…”

DC Series Arc Fault Detection Algorithm for Distributed Energy Resources Using Arc Fault Impedance Modeling

“…In previous research, several algorithms have been invented to detect DC series arc fault condition. In [14]- [17], time domain analysis was introduced to detect the arc fault condition, which uses current and voltage information. These methods provide fast detection speeds with simple circuits and algorithms, but they are susceptible to switching noise and load variation.…”