邓 磊,刘桂华,邓 豪,周炳宏.三维点云分割的交联聚乙烯电缆接头参数测量[J].电子测量与仪器学报,2022,36(9):197-207
三维点云分割的交联聚乙烯电缆接头参数测量
Parameter measurement of cross-linked polyethylene cable jointbased on three-dimensional point cloud segmentation
  
DOI:
中文关键词:  电缆接头  参数测量  三维点云分割  半径方差之比  法向量轴线夹角
英文关键词:cable joint  parameter measurement  three-dimensional point cloud segmentation  ratio of radius variance  angle of normal axis
基金项目:广东电网公司广州供电局委托项目(080044KK52190002)、四川省科技厅重点研发项目(2021YFG0380)资助
作者单位
邓 磊 1. 西南科技大学信息工程学院,2. 特殊环境机器人技术四川省重点实验室 
刘桂华 1. 西南科技大学信息工程学院,2. 特殊环境机器人技术四川省重点实验室 
邓 豪 1. 西南科技大学信息工程学院,2. 特殊环境机器人技术四川省重点实验室 
周炳宏 1. 西南科技大学信息工程学院,2. 特殊环境机器人技术四川省重点实验室 
AuthorInstitution
Deng Lei 1. School of Information Engineering, Southwest University of Science and Technology,2. Key Laboratory of Special Environment Robotics of Sichuan Province 
Liu Guihua 1. School of Information Engineering, Southwest University of Science and Technology,2. Key Laboratory of Special Environment Robotics of Sichuan Province 
Deng Hao 1. School of Information Engineering, Southwest University of Science and Technology,2. Key Laboratory of Special Environment Robotics of Sichuan Province 
Zhou Binghong 1. School of Information Engineering, Southwest University of Science and Technology,2. Key Laboratory of Special Environment Robotics of Sichuan Province 
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中文摘要:
      针对现有参数测量方法难以对交联聚乙烯电缆接头各参数进行有效测量的问题,提出了一种基于三维点云分割的电 缆接头参数测量方法。 该方法先用半径滤波及随机采样一致性(random sample consensus, RANSAC)算法对复合式三维扫描仪 获取的电缆接头点云进行噪声点去除及坐标摆正预处理。 其次,使用 RANSAC 算法对电缆接头点云进行圆拟合,并根据区域 交界处相邻拟合圆半径方差之比的突变特性实现粗分割,得到多个包含区域交界点的局部点云。 然后,使用主成分分析法对局 部点云进行法向量估计,并根据小片点云轴线夹角在区域交界点处的跳变特性及自适应阈值算法,得出各条状点云上的区域交 界值。 接着,对多个条状点云所得同一区域交界值进行统计分析实现电缆接头点云的精分割,完成参数测量。 对多根电缆接头 进行的测量实验结果表明,所提方法的绝对误差小于 1. 0 mm,相对误差小于 4%,说明了该方法用于交联聚乙烯电缆接头参数 测量的有效性与准确性。
英文摘要:
      Aiming at the problem that the existing parameter measurement methods are difficult to effectively measure the parameters of cross-linked polyethylene cable joint, a cable joint parameter measurement method based on three-dimensional point cloud segmentation is proposed. Firstly, radius filtering and random sample consensus (RANSAC) algorithm are used to remove the noise points and preprocess the coordinate alignment of the cable joint point cloud obtained by the composite 3D scanner. Then, the RANSAC algorithm is used to fit the cable joint point cloud to a circle, and the rough segmentation is realized according to the mutation characteristic of the ratio of radius variance of adjacent fitting circles at the regional junction, so as to obtain multiple local point clouds containing regional junction points. Next, the normals of the local point clouds were estimated using principal component analysis, and the regional junction values were derived from the jump characteristics of the axial angles of the point clouds at the regional junction points and the adaptive threshold algorithm. Finally, a statistical analysis of the junction values of the same area obtained from multiple strip point clouds was carried out to achieve a fine segmentation of the cable joint point cloud and complete the parameter measurement. The results of the measurement experiments on several cable joints show that the absolute error of the proposed method is less than 1. 0 mm and the relative error is less than 4%, which demonstrates the validity and accuracy of the method for measuring the parameters of cross-linked polyethylene cable joint.
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