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Arc-fault detector algorithm evaluation method utilizing prerecorded arcing signatures

机译:利用预录电弧特征的电弧故障检测器算法评估方法

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The 2011 National Electrical Code® Article 690.11 requires photovoltaic systems on or penetrating a building to include a DC arc-fault protection device. In order to satisfy this requirement, new Arc-Fault Detectors (AFDs) are being developed by multiple manufacturers including Sensata Technologies. Arc-fault detection algorithms often utilize the AC noise on the PV string to determine when arcing conditions exist in the DC system. In order to accelerate the development and testing of Sensata Technologies'' arc-fault detection algorithm, Sandia National Laboratories (SNL) provided a number of data sets. These prerecorded 10 MHz baseline and arc-fault data sets included different inverter and arc-fault noise signatures. Sensata Technologies created a data evaluation method focused on regeneration of the prerecorded arcing and baseline test data with an arbitrary function generator, thereby reducing AFD development time.
机译:2011年《国家电气法规》第690.11条要求建筑物上或贯穿建筑物的光伏系统必须包括直流电弧故障保护装置。为了满足此要求,包括Sensata Technologies在内的多家制造商正在开发新的电弧故障检测器(AFD)。电弧故障检测算法通常利用PV串上的交流噪声来确定直流系统中何时存在电弧条件。为了加快Sensata Technologies的电弧故障检测算法的开发和测试,桑迪亚国家实验室(SNL)提供了许多数据集。这些预先记录的10 MHz基线和电弧故障数据集包括不同的逆变器和电弧故障噪声信号。 Sensata Technologies创建了一种数据评估方法,该方法专注于使用任意函数发生器来重新生成预先记录的电弧放电和基准测试数据,从而缩短了AFD开发时间。

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