Automatic Detection of Inactive Solar Cell Cracks in Electroluminescence Images

S. Spataru, P. Hacke, D. Sera
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引用次数: 2

Abstract

Inactive solar cell regions resulted from their disconnection from the electrical circuit of the cell are considered to most severe type of solar cell cracks, causing the most power loss. In this work, we propose an algorithm for automatic determination of the electroluminescence (EL) signal threshold level corresponding these inactive solar cell regions. The resulting threshold enables automatic quantification of the cracked region size and estimation of the risk of power loss in the module. We tested the algorithm for detecting inactive cell areas in standard mono and mc-Si, showing the influence of current bias level and camera exposure time on the detection. Last, we examined the correlation between the size of the detected solar cell cracks and the power loss of the module.
电致发光图像中非活性太阳能电池裂纹的自动检测
由于与电池电路断开而导致的非活性太阳能电池区域被认为是太阳能电池最严重的裂缝类型,造成最大的功率损失。在这项工作中,我们提出了一种自动确定这些非活性太阳能电池区域对应的电致发光(EL)信号阈值水平的算法。由此产生的阈值可以自动量化裂纹区域大小并估计模块中功率损耗的风险。我们测试了该算法在标准单色和mc-Si中检测非活性细胞区域,显示了电流偏置电平和相机曝光时间对检测的影响。最后,我们研究了检测到的太阳能电池裂纹的大小与组件的功率损耗之间的关系。
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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