| 基于U-Net网络和图像分割的无人机输电线路绝缘子缺失故障检测方法 |
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| 引用本文：朱开放，陆欣，梁开朗，李卓鹏，覃周培.基于U-Net网络和图像分割的无人机输电线路绝缘子缺失故障检测方法[J].计算技术与自动化,2025,(3):106-110 |
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| 中文摘要:绝缘子所处的环境较为恶劣，容易产生缺失和失效的问题，导致输电线路短路等故障，为此，研究基于U-Net网络和图像分割的无人机输电线路绝缘子缺失故障检测方法。通过无人机自主巡检输电线路，在巡检过程中获取图像数据；采用图像分割技术预处理图像数据，将原始图像分割成多个大小相似的小区域，在不同的像素区域内提取出绝缘子缺失数据特征；将处理好的图像数据与分离的绝缘子缺失数据，放置于U-Net网络进行训练，在不断调整和优化网络参数的过程中，实现输电线路绝缘子缺失数据的分类和定位，完成对输电线路绝缘子缺失故障的检测。实验结果表明此方法具有应用价值。 |
| 中文关键词:U-Net网络 图像分割 无人机巡检 输电线路 绝缘子缺失故障 |
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| A Fault Detection Method for Missing Insulators in Unmanned Aerial Vehicle Transmission Lines Based on U-Net Network and Image Segmentation |
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| Abstract:The environment in which insulators are located is relatively harsh, which can easily lead to missing and failure problems, resulting in faults such as short circuits in transmission lines. Therefore, a detection method for missing insulators in unmanned aerial vehicle transmission lines based on U-Net network and image segmentation is studied. Obtain image data during the autonomous inspection of power transmission lines by drones; Using image segmentation technology to preprocess image data, the original image is segmented into multiple small regions of similar size, and insulator missing data features are extracted in different pixel regions; The processed image data and separated missing insulator data are placed on the U-Net network for training. During the process of continuously adjusting and optimizing network parameters, the classification and localization of missing insulator data on transmission lines are achieved, and the detection of missing insulator faults on transmission lines is completed. The experimental results indicate that it has practical value. |
| keywords:U-Net network image segmentation drone inspection transmission lines insulator missing fault |
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