Data for: Hydrophobicity Classification of Composite Insulators Based on Convolutional Neural Networks

By applying the spray method (IEC Standard 62073), about 4500 photos were collected and are available online, from all hydrophobicity classes using distilled water-ethyl alcohol as spraying solution. The pictures of the seven different hydrophobicity classes were split into three separate sets for each hydrophobicity class. The first one consisting of 400 instances of each class (400 × 7 = 2800 photos) was used for the training of the networks. The second one consisting of 100 instances of each class (100 × 7 = 700 photos) was used for the evaluation-validation of the learning course and the comparison of the different models. The last one with 122-165 different instances of each class (980 photos) was used for the final assessment of our chosen model.

通过采用喷雾法（IEC标准62073），共收集了约4500张照片，这些照片均采用蒸馏水-乙醇混合液作为喷雾溶液，并已上网发布，涵盖了所有亲水性类别。七种不同亲水性类别的图片被划分为每个类别三个独立的集合。其中，第一个集合包含每个类别的400个实例（400 × 7 = 2800张照片），用于网络的训练。第二个集合包含每个类别的100个实例（100 × 7 = 700张照片），用于学习过程的评估与验证，以及不同模型的比较。最后一个集合包含每个类别122至165个不同的实例（共980张照片），用于对我们所选模型的最终评估。