Gaoya dianqi目前基于卷积神经网络将复合绝缘子喷水图像进行整体憎水性分类的方法对于图像局部的憎水性关注度不足，因此本文提出了一种基于目标检测算法的复合绝缘子表面憎水性判别方法。首先取样不同形态的喷水图片共5 800张，根据水珠形貌和接触角提出了单独针对水珠的分类标准。之后采用以SE-Resnet为骨架网络的Faster R-CNN对表面水珠进行分类，并获得了基于目标检测算法的21个水珠局部特征参数。为了兼顾图片全局特性，同时基于数字图像处理构建了12个与水珠亮斑面积和形态相关的全局参数。最后通过特征筛选 ...
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