【摘要】 传统的复合绝缘子憎水性等级分类主要依靠电网工作人员在高空下进行，受到环境、天气等因素的影响，检测质量难以保证，工作效率低下。提出一种基于KNN算法的复合绝缘子憎水性等级分类方法，并对KNN算法进行试验，选择最合适的参数进行复合绝缘子憎水性等级分类。试验结果表明，当K=8，使用曼哈顿距离，对复合绝缘子憎水性等级分类准确率最高，达到86.41%。更多还原

【Abstract】 Since the traditional classification of hydrophobicity grades of composite insulators mainly relies on power grid staff working at high altitudes,it’s difficult to ensure the quality of testing affected by factors such as environment and weather,resulting in low work efficiency.In this paper,a new classification method of composite insulator hydrophobicity based on KNN algorithm is proposed and the KNN algorithm is tested to select the most suitable parameters to classify the hydrophobicity grade of composite insulators. The experimental results show that,when K is equal to 8 and Manhattan distance is used,the accuracy of classifying the hydrophobicity grade of composite insulators is the highest,reaching 86.41%.更多还原