【摘要】 电力变压器的关键尺寸测量是其装配制造、运输安装过程中重要一环，现有测量方法操作繁琐且效率较低。为此，本文提出了一种适用于110 kV油浸式电力变压器关键尺寸视觉检测方法，该方法利用YOLO目标检测算法、Grabcut图像分割算法实现关键组部件的智能检测与分割，然后基于双目立体视觉原理实现套管相间距离及变压器最大截面外形尺寸等关键尺寸的测量。本文搭建了110 kV油浸式电力变压器外观缩比模型，试验分析了拍摄距离和角度等因素对电力变压器关键尺寸视觉检测的影响。结果表明，本文基于缩比模型试验实现了在不同拍摄距离与角度下变压器关键尺寸的视觉检测，验证了该方法的有效性。本文方法可以为110 kV油浸式电力变压器现场尺寸测量提供参考。更多还原

【Abstract】 The measurement of key dimensions of power transformers is an important part of their assembly, manufacturing, transportation, and installation processes. Existing measurement methods are cumbersome and inefficient. Therefore, this paper proposes a visual detection method for key dimensions of 110 kV oil-immersed power transformers. This method utilizes the YOLOv5 object detection algorithm and Grabcut image segmentation algorithm to achieve intelligent detection and segmentation of key components. Then, based on the principle of binocular stereo vision, key dimensions such as the distance between bushings and the maximum cross-sectional dimension of the transformer are measured. This paper establishes a scaled model of the appearance of 110 kV oil-immersed power transformers, and analyzes the effects of factors such as shooting distance and angle on visual inspection of key dimensions of power transformers through experiments. The results indicate that this paper achieved visual detection of key dimensions of transformers under different shooting distances and angles based on scaled model experiments, verifying the effectiveness of this method. This method can provide reference for on-site dimension measurement of 110 kV oil-immersed.更多还原