Transformer terminal feature recognition and positioning method based on binocular vision and image processing algorithm

Lingying Chen, Yue Zhao, Xing Li
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Abstract

Based on binocular vision and image processing algorithm, the recognition and location of high voltage side and low voltage side of transformer were completed for transformer automatic wiring positioning platform. On the basis of binocular vision calibration and 3D point cloud reconstruction, P3P algorithm was used to complete the positioning of transformer operation space coordinate system. Based on the image threshold segmentation algorithm, the position of transformer high voltage terminal, low voltage terminal, and transformer rotation angle were identified on the basis of 3d point cloud data. The target position information was provided for transformer automatic wiring device.
基于双目视觉的变压器终端特征识别与定位方法及图像处理算法
基于双目视觉和图像处理算法,为变压器自动布线定位平台完成了变压器高压侧和低压侧的识别和定位。在双目视觉标定和三维点云重建的基础上,采用P3P算法完成变压器运行空间坐标系的定位。基于图像阈值分割算法,基于三维点云数据识别变压器高压端子、低压端子位置和变压器旋转角度。为变压器自动布线装置提供目标位置信息。
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