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光伏用电致发光缺陷检测仪成像系统性能评估方法

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为提高电致发光缺陷检测仪成像系统性能评估过程中线对图像判别的准确率与重复性,文中参考相关标准,采用专用算法实现对线对图像的自动识别,并与人眼判别结果进行比较.同时建立模型,采用蒙特卡洛法评估算法判别线对图像的不确定度的方法,分析空间分辨率测试板加工误差、图像倾斜角度、图像灰度均匀度三个影响因素对算法判别的影响.结果表明,相对于人眼判别,采用算法判别的准确率和重复性较好,准确率达 98%,重复性达 100%.针对示例,采用蒙特卡洛法评定的算法判别不确定度结果为 0.0387 lp/mm.总体来说,相对于人眼判别,采用算法进行判别能在很大程度上提高电致发光缺陷检测仪成像系统性能评估过程中线对图像判别的准确率与重复性.
Performance Evaluation of Imaging System of Electroluminescent Defect Detector for Photovoltaic
In order to improve the accuracy and repeatability of line pair image discrimination in the performance evaluation process of the electroluminescent defect detector imaging system.Refer to relevant standards,a special algorithm is used to realize automatic discrimination of line pair images,and the results are compared with manual discrimination by human eyes.At the same time,a model is established,and the method of using Monte Carlo method to evaluate the uncertainty of line pair image is studied,and the influence of three factors on algorithm discrimination results are analyzed,including the machining accuracy of the spatial resolution test board,the image tilt angle,and the uniformity of image.The results show that the accuracy and repeatability of the algorithm discrimination are better than manual discrimination by human eyes,with the accuracy of 98%and the repeatability of 100%.For the example given,the uncertainty of the algorithm discrimination is 0.0387 lp/mm.In general,compared with human eye discrimination,algorithms discrimination can greatly improve the accuracy and repeatability of line pair image discrimination in the performance evaluation process of the electroluminescent defect detector imaging system,and the uncertainty of the discrimination results is low.

PhotovoltaicElectroluminescent defect detectorSpatial resolutionMonte carlo method

徐彩军

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福建省特种设备检验研究院,福建 福州 350008

光伏 电致发光缺陷检测仪 空间分辨率 蒙特卡洛法

2024

市场监管与质量技术研究
福建省标准化研究院

市场监管与质量技术研究

影响因子:0.299
ISSN:2097-0870
年,卷(期):2024.(4)
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