摘要
绝缘子污秽等级的准确识别是污闪防治的有效途径。红外和可见光图像分别表征了污秽绝缘子的表面温度和色彩分布,可从不同角度反映绝缘子的污秽状态,该文提出了基于红外和可见光图像信息融合的绝缘子污秽等级识别方法。建立并求解了湿污绝缘子发热数学模型,得到了绝缘子表面温度分布;通过实验获取绝缘子红外及可见光图像,经图像分割后,提取了绝缘子盘面红外与可见光特征并用Fisher判别法进行选择;将选出的特征与环境湿度、照度组合成为特征向量,并使用贝叶斯决策理论对其进行特征级信息融合,识别绝缘子污秽等级;最后对现场样本进行了识别。实验结果显示,图像信息融合提高了绝缘子污秽等级识别准确率,现场测试结果准确,为准确识别现场绝缘子污秽等级提供了新方法。
Flashover can be reduced if insulator contamination grade is accurately discriminated. Infrared images and visible images show temperature and color features of insulators respectively, which describe insulator contamination grades from different perspective. This paper presented a method to discriminate insulator contamination grades, using information fusion of infrared images and visible images. Firstly, heating models of contaminated wetted insulators were established and solved by numerical analysis method. From the models, the surface temperature distribution was found out. Secondly, infrared and visible insulator images were obtained in laboratory. Thirdly, after image processing, temperature and color features were extracted and screened by Fisher criterion, after which feature vectors consist of relative humidity, illumination and the screened features were obtained. Finally, Bayes theorem was used for information fusion on feature level with the feature vectors, and insulator contamination grades were discriminated. Experimental results show that information fusion of infrared and visible images achieve much higher accuracy in insulator contamination grades discrimination. Furthermore, on-site tests verify the feasibility of this method. This paper provides a new and workable method for accurate discrimination of insulator contamination grades.
出处
《中国电机工程学报》
EI
CSCD
北大核心
2016年第13期3682-3691,3389,共10页
Proceedings of the CSEE
基金
国家自然科学基金项目(51177109
51577135)
电力设备电气绝缘国家重点实验室资助项目(EIPE14211)~~
