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A Series DC Arc Fault Detection Algorithm Based on PV Operating Characteristics and Detailed Extraction of Pink Noise Behavior

机译:一种基于光伏操作特性的DC电弧故障检测算法及粉红色噪声行为的详细提取

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Traditional arc fault detection methods focus on the time domain or the frequency domain of the current signal as an indicator of a possible arc fault event. However, the pink noise generated by the arc fault is usually observed only as an increase in energy and not specifically characterized, leading to unwanted tripping from other arc-like transients. In this research, the pink noise analysis, along with unique properties of the PV operating point of both the instantaneous current and voltage signal, is used to distinguish arc faults from other noisy loads or PV degradations. Experimental results validate that the algorithm successfully detects series DC arc faults.
机译:传统的电弧故障检测方法侧重于当前信号的时域或频域作为可能的电弧故障事件的指示。 然而,由电弧故障产生的粉红色噪声通常仅被观察到能量的增加而不是特定表征,导致来自其他电弧瞬变的不需要的跳闸。 在该研究中,粉红色噪声分析以及瞬时电流和电压信号的PV操作点的独特性能,用于区分来自其他嘈杂的负载或PV降级的电弧故障。 实验结果验证了该算法成功检测DC电弧故障。

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