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A Monocular Vision-Based Framework for Power Cable Cross-Section Measurement

机译:基于单眼视觉的电力电缆横截面测量框架

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摘要

The measurements of the diameter of different layers, the thickness of different layers and the eccentricity of insulation layer in the cross-section of power cables are important items of power cable test, which currently depend on labor-intensive manual operations. To improve efficiency, automatic measurement methods are in urgent need. In this paper, a monocular vision-based framework for automatic measurement of the diameter, thickness, and eccentricity of interest in the cross-section of power cables is proposed. The proposed framework mainly consists of three steps. In the first step, the images of cable cross-section are captured and undistorted with the camera calibration parameters. In the second step, the contours of each layer are detected in the cable cross-section image. In order to detect the complete and accurate contours of each layer, the structural edges in the cross-section image are firstly detected and divided into individual layers, then unconnected edges are connected by arc-based method, and finally contours are refined by the proposed break detection and grouping (BDG) and linear trend-based correction (LTBC) algorithm. In the third step, the monocular vision-based cross-section dimension measurement is accomplished by placing a chessboard coplanar with the power cable cross-section plane. The homography matrix mapping pixel coordinates to chessboard world coordinates is estimated, and the diameter, thickness and eccentricity of specific layers are calculated by homography matrix-based measurement method. Simulated data and actual cable data are both used to validate the proposed method. The experimental results show that diameter, minimum thickness, mean thickness and insulation eccentricity of simulated image without additive noise are measured with root mean squared error (RMSE) of 0.424, 0.103 and 0.063 mm, and 0.002, respectively, those of simulated image with additive Gaussian noise and salt and pepper noise are measured with RMSE of 0.502, 0.243 and 0.058 mm and 0.001. Diameter, minimum thickness and mean thickness of actual cable images are measured with average RMSE of 0.768, 0.308 and 0.327 mm. The measurement error of insulation eccentricity of actual cable image is comparatively large, and the measurement accuracy should be improved.
机译:电力电缆横截面中不同层的直径,不同层的厚度和绝缘层的偏心率是电力电缆测试的重要项目,目前取决于劳动密集型手动操作。为了提高效率,自动测量方法迫切需要。本文提出了一种用于自动测量电力电缆横截面的直径,厚度和偏心的基于单眼视觉的框架。拟议的框架主要由三个步骤组成。在第一步中,通过相机校准参数捕获电缆横截面的图像并不静置。在第二步中,在电缆横截面图像中检测每个层的轮廓。为了检测每层的完整和准确的轮廓,首先检测横截面图像中的结构边缘并分成各个层,然后通过基于弧形的方法连接未连接的边缘,最后通过提出的轮廓来改装轮廓。断点检测和分组(BDG​​)和基于线性趋势校正(LTBC)算法。在第三步骤中,通过将棋盘共面与电力电缆横截面平面放置来实现单像视觉的横截面尺寸测量。估计与棋盘世界坐标坐标的同封矩阵映射像素坐标,并且通过基于矩阵的测量方法计算特定层的直径,厚度和偏心度。模拟数据和实际电缆数据均用于验证所提出的方法。实验结果表明,没有添加到噪声的模拟图像的直径,最小厚度,平均厚度和绝缘偏心,其具有0.424,0.103和0.063mm的根部平均平方误差(RMSE),以及0.002的模拟图像,具有添加剂的模拟图像高斯噪音和盐和辣椒噪声用0.502,0.243和0.058 mm和0.001的RMSE测量。直径,实际电缆图像的最小厚度和平均厚度,平均RMSE为0.768,0.308和0.327mm。实际电缆图像的绝缘偏心的测量误差相对较大,应提高测量精度。

著录项

  • 作者

    Xiaoming Zhang; Hui Yin;

  • 作者单位
  • 年度 2019
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  • 原文格式 PDF
  • 正文语种 eng
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