红外技术2025，Vol.47Issue(10)：1314-1323,10.
基于DTDU-Net的电气设备紫外光斑图像分割
Ultraviolet Spot Image Segmentation of Electrical Equipment Based on DTDU-Net
摘要
Abstract
Segmenting discharge spots in ultraviolet images of electrical equipment helps to quickly locate faulty areas and assess the discharge intensity,thereby providing technical support for maintaining the safe operation of power grid systems.The irregular shape and fuzzy edges of the ultraviolet discharge spot can easily lead to missegmentation and missing segmentation.A DTDU-Net UV discharge spot segmentation method based on an improved U-Net is proposed.First,a residual structure and deformable convolution were introduced into the encoder to enhance the feature extraction capability and reduce missing segmentation.Second,the U-Net skip connection was replaced with a channel cross-fusion transformer to effectively capture the cross-channel interactions and improve spot mis-segmentation.Finally,in the decoder part,an ultra-lightweight dynamic up-sampler,DySample,is used to replace the original up-sampling operation,which can better retain the image details and alleviate the problem of missing segmentation.The experimental results showed that the average crossover ratio of the improved network for UV spot segmentation was 95.17％,and the average accuracy was 96.79％,which were improved by 6.32％and 6.77％,respectively,compared with those of U-Net.Additionally,the segmentation effect was good.关键词
紫外图像/U-Net/残差结构/可变形卷积/transformer/DySampleKey words
ultraviolet image/U-Net/residual structure/deformable convolution/transformer/DySample分类
信息技术与安全科学引用本文复制引用
张贝贝,霍思佳,巨思远,秦伦明,边后琴,王悉..基于DTDU-Net的电气设备紫外光斑图像分割[J].红外技术,2025,47(10):1314-1323,10.基金项目
国家自然科学基金面上项目(62073024). （62073024）
