大尺寸薄壳物体表面的三维光学自动检测  

3D Auto-Inspection for Large Thin-Wall Object

作　　者：刘晓利[1] 彭翔[1] 殷永凯[1] 李阿蒙[1] 张承功[1] 何懂[1] 

机构地区：[1]深圳大学光电工程学院,教育部、广东省光电子器件与系统重点实验室,广东深圳518060

出　　处：《光学学报》2011年第3期120-126,共7页Acta Optica Sinica

基　　金：国家自然科学基金(60775021);深圳大学科技计划项目(000018);精密测试技术及仪器国家重点实验室(天津大学)-光电子器件与系统教育部重点实验室(深圳大学)联合开放课题资助课题

摘　　要：报道一种大型薄壳物体的智能光学三维测量以及自动在线检测方法,利用三节点光学测量传感器网络实现了大型薄壳物体内外表面数据的三维重建、特征尺寸获取及计算机辅助设计(CAD)模型的比对。提出一种有效的三维多节点传感器测量网络的系统标定方法,可同时完成整体测量系统在大尺度测量空间的现场标定以及各个三维节点测量传感器的标定。提出一种采用多传感器标定信息与最近点迭代方法(ICP)相结合的多视点深度测量数据的匹配方法。在此基础上,利用ICP将测量的三维模型数据与CAD模型数据相匹配,并获取误差分布图。理论分析和实验证明了所提出的测量方法的有效性。We propose an optical measurement technique devoted to on-line inspection of large-scale and thin-wall objects.The proposed approach is based on a measurement network that consists of three-node optical sensors.With this specifically designed measurement network system,we can achieve the inspection tasks such as multi-view range-data acquisition,registration,and integration while it is also possible to make a comparison of reconstructed model with the computer-aided-design（CAD） model to precisely determine the error distribution on each external and internal facet walls.An on-line calibration scheme for multiple-node sensors based on phase-mapping combined with photogrammetric technique is also presented and verified by experiments.Furthermore,the registration of multi-view range-data can be achieved using the calibrated parameters and iterative closest points（ICP） algorithm.Moreover,we also employ ICP algorithm for the alignment of reconstructed model with measured data with the nominal CAD model,and then the dimension computation and error comparison can be easily acquired.Both the theoretical analysis and the experimental results show the effectiveness of the proposed approach.

关 键 词：光学检测 薄壳物体 多传感器标定 深度图像 全局空间匹配 

分 类 号：TP242[自动化与计算机技术—检测技术与自动化装置]