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

机译:检测和识别电弧电流故障的最新方法

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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.
机译:本文回顾了用于检测和识别电弧电流(包括电弧电流故障)的方法。审查的方法分为时域,频域和时频方法。时域方法提取肩膀(零交叉点附近的电流的零值),尖峰和跳跃,异常幅度(低于或高于正常值)以及电流的高变化率。频域方法提取高频成分,谐波成分,次谐波成分和互相关指标。时频方法提取包含非平稳频率分量的高频子带,这些分量可能具有非平稳相位。实施了这三种方法来测试其准确性,计算要求以及对系统参数的敏感性。这些测试是通过对正常和动态情况,常规故障以及具有高或低电弧分量的电流进行离线处理而进行的。测试结果为测试方法提供了性能比较。

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