Identifying DC Series and Parallel Arcs Based on Deep Learning Algorithms

Arc phenomena are usually related to the undesired disengagement of two electrical connections. The emission power discharge from failure arc may damage wiring and can present a fire hazard. Numerous studies have been proposed detect events quickly isolate them an system. DC faults often sorted into types: series parallel arcs. A be outcome discharging links in wiring. By contrast, occurs between electric wires, or link ground, owing contamination poor isolation. currents system with fault considerably greater when nature than is nature. In this paper, activities network investigated for duration failures both time frequency domains. arcing behavior selected allow identification sorting arcs accurate reliable manner useful protection schemes. process used here based on data different domains, such as load current voltage. study, eight learning techniques aim detecting faults. behaviors were studied various We voltage characteristics statistic categorizing given failure. This study could beneficial enhance stability reliability arc-fault detectors.