State-of-the-Art Methods for Detecting and Identifying Arcing Current Faults

S. Saleh, M. Valdes, C. Mardegan, B. Alsayid
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引用次数: 4

Abstract

This paper reviews approaches used to detect and identify arcing currents, including arcing current faults. The reviewed approaches are categorized as the time-domain, frequency-domain, and time-frequency approaches. The time-domain approach extracts shoulders (zero values of the current around zero crossing points), spikes and jumps, abnormal magnitudes (lower or higher than normal), and high rate of change of the current. The frequency-domain approach extracts the high frequency components, harmonic components, sub-harmonic components, and cross-correlation indicator. The time-frequency approach extracts high frequency sub-bands that contain nonstationary frequency components, which may have non-stationary phases. The three approaches are implemented to test their accuracy, computational requirements, and sensitivity to system parameters. These tests are performed by off-line processing of currents that are collected for normal and dynamic conditions, conventional faults, and currents with high or low arcing components. Test results provide a performance comparison for the tested approaches.
检测和识别电弧电流故障的最新方法
本文综述了用于检测和识别电弧电流的方法,包括电弧电流故障。所回顾的方法分为时域、频域和时频方法。时域方法提取肩部(零交叉点附近的零电流值),尖峰和跳跃,异常幅度(低于或高于正常)以及电流的高变化率。频域法提取高频分量、谐波分量、次谐波分量和互相关指标。时频方法提取包含非平稳频率成分的高频子带,这些分量可能具有非平稳相位。实现了这三种方法,以测试它们的精度、计算要求和对系统参数的敏感性。这些测试是通过离线处理在正常和动态条件下收集的电流、常规故障以及具有高或低电弧分量的电流来进行的。测试结果提供了测试方法的性能比较。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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