A Novel Arc Fault Detector for Early Detection of Electrical Fires

Abstract

Arc faults can produce very high temperatures and can easily ignite combustible materials; thus, they represent one of the most important causes of electrical fires. The application of arc fault detection, as an emerging early fire detection technology, is required by the National Electrical Code to reduce the occurrence of electrical fires. However, the concealment, randomness and diversity of arc faults make them difficult to detect. To improve the accuracy of arc fault detection, a novel arc fault detector (AFD) is developed in this study. First, an experimental arc fault platform is built to study electrical fires. A high-frequency transducer and a current transducer are used to measure typical load signals of arc faults and normal states. After the common features of these signals are studied, high-frequency energy and current variations are extracted as an input eigenvector for use by an arc fault detection algorithm. Then, the detection algorithm based on a weighted least squares support vector machine is designed and successfully applied in a microprocessor. Finally, an AFD is developed. The test results show that the AFD can detect arc faults in a timely manner and interrupt the circuit power supply before electrical fires can occur. The AFD is not influenced by cross talk or transient processes, and the detection accuracy is very high. Hence, the AFD can be installed in low-voltage circuits to monitor circuit states in real-time to facilitate the early detection of electrical fires.

Analysis of the Effects of Arc Volt–Ampere Characteristics on Different Loads and Detection Methods of Series Arc Faults

“…Some time-frequency analysis methods, such as a short-time Fourier transform [15], wavelet transform [11,[16][17][18][19][20][21][22], and Hilbert-Huang transform [23], have also been used for fault arc detection. In addition, some pattern recognition methods have been used to help classify the situation when an arc fault occurs, such as support vector machines [13] and neural networks [11,[20][21]23]. Most of the above methods need to extract the current characteristics under the arc fault condition based on the current waveform at the time of the arc fault and determine whether an arc fault has occurred.…”

“…More studies have used frequency domain analysis methods. A harmonic analysis has been conducted on a specific frequency band of the line current when arc faults occur [10][11][12][13][14]. Some time-frequency analysis methods, such as a short-time Fourier transform [15], wavelet transform [11,[16][17][18][19][20][21][22], and Hilbert-Huang transform [23], have also been used for fault arc detection.…”

Optimal Design of a Band Pass Filter and an Algorithm for Series Arc Detection

“…An arc is a luminous discharge of electricity across an insulating medium, usually accompanied by the partial volatilization of the electrodes [5,6,8]. Owning to the current flowing in the circuit and the high temperature, arcing is one of the main causes of electrical fires.…”

“…It was also confirmed that the series arc faults in a circuit occur due to partial disconnection between cords, loose connection between cord and terminal, and loose connection between outlet and plug. Most of the existing studies about series arcs use the carbon graphite-copper electrode specified in UL 1699 and IEC 62606 to generate the arc signal [5,6,8]. It is an ideal condition, under which the magnitude of arc current is much higher than that of the actual series arc and can be easily detected.…”

“…They operate to de-energize the circuit when an arc fault is detected. However, discrimination of the arc condition is still a challenge for development an arc fault detector [8].…”