摘要
针对传统检测方法不能满足电路板微型元件三维检测的微纳级精度需求,提出基于光谱共焦传感器的电路板元件三维检测方法。先通过光谱共焦传感器扫描电路板采集点云数据,对点云数据滤波后利用欧氏聚类法作分割,再采用基于自适应高斯权重的空间点云平面拟合方法,对分割后的点云数据边缘和内部区域分配不同的权值,减小边缘噪声点对拟合精度的影响,最后通过拟合点云数据计算电路板元件三维尺寸信息。对大量电路板微型元件进行三维检测,最大误差为7.95μm,最小误差为1.46μm,满足电路板元件高精度检测要求,具有较强的实际应用价值。
Aiming at the fact that traditional detection methods cannot meet the micro-nano precision requirements for 3D detection of micro-components on circuit boards,a 3D detection method for circuit board components based on spectral confocal sensors is proposed. First,the point cloud data is collected by scanning the circuit board with the spectral confocal sensor,the point cloud data is filtered and then segmented by the Euclidean clustering method,and then the spatial point cloud plane fitting method based on adaptive Gaussian weight is used. The edge and inner area of cloud data are assigned different weights to reduce the influence of edge noise points on the fitting accuracy. Finally,3D size information of circuit board components are calculated by fitting the point cloud data. Three-dimensional detection of a large number of micro components on circuit boards,the maximum error is7.95μm,and the minimum error is 1.46μm,which meets the requirements of high-precision detection of circuit board components and has strong practical application value.
作者
张志荣
洪汉玉
章秀华
ZHANG Zhirong;HONG Hanyu;ZHANG Xiuhua(Hubei Provincial Key Laboratory of Optical Information and Pattern Recognition,Wuhan Institute of Technology,Wuhan 430205;Hubei Province Video Image and HD Projection Engineering Technology Research Center,Wuhan Institute of Technology,Wuhan 430205;School of Electrical Information,Wuhan Institute of Technology,Wuhan 430205)
出处
《计算机与数字工程》
2022年第9期2102-2108,共7页
Computer & Digital Engineering
基金
国家自然科学基金项目(编号:62171329)资助。
关键词
三维检测
微纳级
光谱共焦
自适应高斯权重
空间点云平面拟合
3D detection
micro-nano level
spectral confocal
adaptive Gaussian weight
spatial point cloud plane fitting
