基于三维点云无网格处理的大型锻件尺寸特征曲线重建
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摘要
大型锻件是制造重大装备的基础件，锻件特征尺寸的精确提取对提高锻件制造过程中原材料利用率、改善产品质量和提高产品合格率都具有重要作用。通过尺寸三维点云重建大型锻件的三维特征曲线，正在逐步成为大型锻件尺寸三维测量领域研究的热点和难点。本课题以大型锻件尺寸三维点云的强噪声、海量性和局部化特点为基础，运用三维点云无网格处理理论，对大型锻件尺寸三维特征曲线的精确、快速、可靠重建问题进行研究。
首先，以各向异性滤波理论为基础，构建基于采样点微分几何信息的大型锻件尺寸三维点云各向异性消噪模型，实现三维点云消噪核函数的形状、方向的自适应调整；基于该模型设计大型锻件尺寸三维点云无网格消噪算法，实现在消除三维点云中强噪声的同时锻件结构特征的有效保持，为大型锻件尺寸特征曲线的精确重建奠定基础。
其次，将测度理论和离散微分几何估计理论相结合，建立用于定量描述采样点微分几何相似性的信息相似度模型，并以信息相似度最大为原则构建收缩点对；利用采样点与邻域点间的信息相似度构建信息相似度加权二次误差测度，并通过该误差测度最小化实现点对收缩最优坐标的求解；以最小加权二次误差作为点对收缩代价，基于迭代收缩代价最小点对的思想，设计大型锻件尺寸三维点云无网格精简算法，实现精简三维点云的同时有效保持锻件的结构特征，为大型锻件尺寸特征曲线的精确、快速重建提供保障。
进一步，基于核密度估计理论，建立三维点云拼接测度函数，将BFGS拟牛顿优化算法与模拟退火算法相结合进行测度函数变尺度寻优，提出基于测度函数变尺度寻优的三维点云拼接算法，以解决三维点云拼接精度与收敛区间之间的矛盾，为大型锻件尺寸特征曲线的完整重建奠定基础；将张量分解和多尺度分析有机结合，建立三维点云多尺度张量特征指标，在利用多尺度张量特征指标进行采样点进行特征识别的基础上，通过最小生成森林和伪特征点投影重建点云特征曲线，进而实现大型锻件尺寸特征曲线的可靠重建。
最后，在激光扫描三维测量平台上进行锻件尺寸三维测量，通过对测得三维点云进行无网格处理重建锻件尺寸特征曲线，验证课题提出算法的精确性、快速性和可靠性。
Large forgings are the fundmental part of the major equipments. Precise extractionof the size of the large forgings plays important roles in improving the utilization of rawmaterials, improving product quality and increasing the rate of qualified products.Reconstruction the feature curve of the workpiece from measured3D point clouds isgradually becoming a hot and difficult point in the field of measurements of largeforgings size. Based on the strong noises, mass and localized characteristics of the3Dpoint clouds of large forgings size, utlizing3D point clouds meshless processing theory,the problem of accurate, rapid and reliable reconstruction methods of the feature curve oflarge forgings were researched indepth.
Firstly, based on anisotropic denoising theory, a new3D point clouds anisotropicdenoising model was estiblashed for large forgings3D data, using the differentialgeometric information of the sampled points. The shape and orientation of the denoisingkernel function were ajusted adaptivly. A new3D point clouds denoising alghrithm wasproposed for large forgings based on the new model. The strong noises are smoothed,meanwhile the feature feature of the forgings are preserved, laying the foundation for theaccurate reconstruction of the feature curve of large forgings.
Secondly, measure theory and estimation theory of discrete differential geometrywere combined together. The information similarity model was established toquantitativly describe the differential geometrical similarity between the the sampledpoints. The contract pairs were constructed under the princple of maximum informationsimilarity. The information similarity weighted quadric error matric was construced foreach sampled point based on the information similarity between the sampled point and itsneighbors. The optimal position of the contracted pair was solved by minmizing theweighted error matric, the cost of the contraction was evaluated by the minmum value ofthe weighted error matric. A3D point clouds meshless simplification algorithm wasproposed for larging forgings based on the concept of iteratively contracting the least costpairs, providing guarantees for the accurate and rapid structural curve reconstruction of large forgings.
Thirdly, a new3D point clouds registration measue was proposed based on kerneldensity estimation theory. The BFGS quasi-Newton optimization and simulated annealingalgorithm was combined together to search the maxmum point of the measure in varyingscaled manner. A robust variant scale3D point clouds registration algorithm was proposedbased on the principle, in order to solve the conflicts between accuracy and convergenceinterval of classical registration algorithms, laying the foundation for the integratedreconstruction of the feature curve of large forgings. Tensor decomposition theory andmulti-scale analysis theory were combined together. Multi-scaled tensor characteristicindex was constructed to describe the characteristics of the sampled points. Based on thecapability of the Multi-scaled tensor characteristic index in distinguishing the featurepoints, the minmum spanning forest algorithm was usd to connect the feature points andconstruct the featured polygonal lines. Furthermore, polygonal lines were smoothed bymoving least squares algorithm, and the fake feature points were projected to thesmoothed curves. In such way, the featured curves of large forgings were constructedreliably.
Finaly,3D measurement of the simulated forgings was undergone by the laserscanning3D measure platform. The experimental results reveals that the accuracy,rapidity and reliablity of the proposed methods.
首先，以各向异性滤波理论为基础，构建基于采样点微分几何信息的大型锻件尺寸三维点云各向异性消噪模型，实现三维点云消噪核函数的形状、方向的自适应调整；基于该模型设计大型锻件尺寸三维点云无网格消噪算法，实现在消除三维点云中强噪声的同时锻件结构特征的有效保持，为大型锻件尺寸特征曲线的精确重建奠定基础。
其次，将测度理论和离散微分几何估计理论相结合，建立用于定量描述采样点微分几何相似性的信息相似度模型，并以信息相似度最大为原则构建收缩点对；利用采样点与邻域点间的信息相似度构建信息相似度加权二次误差测度，并通过该误差测度最小化实现点对收缩最优坐标的求解；以最小加权二次误差作为点对收缩代价，基于迭代收缩代价最小点对的思想，设计大型锻件尺寸三维点云无网格精简算法，实现精简三维点云的同时有效保持锻件的结构特征，为大型锻件尺寸特征曲线的精确、快速重建提供保障。
进一步，基于核密度估计理论，建立三维点云拼接测度函数，将BFGS拟牛顿优化算法与模拟退火算法相结合进行测度函数变尺度寻优，提出基于测度函数变尺度寻优的三维点云拼接算法，以解决三维点云拼接精度与收敛区间之间的矛盾，为大型锻件尺寸特征曲线的完整重建奠定基础；将张量分解和多尺度分析有机结合，建立三维点云多尺度张量特征指标，在利用多尺度张量特征指标进行采样点进行特征识别的基础上，通过最小生成森林和伪特征点投影重建点云特征曲线，进而实现大型锻件尺寸特征曲线的可靠重建。
最后，在激光扫描三维测量平台上进行锻件尺寸三维测量，通过对测得三维点云进行无网格处理重建锻件尺寸特征曲线，验证课题提出算法的精确性、快速性和可靠性。
Large forgings are the fundmental part of the major equipments. Precise extractionof the size of the large forgings plays important roles in improving the utilization of rawmaterials, improving product quality and increasing the rate of qualified products.Reconstruction the feature curve of the workpiece from measured3D point clouds isgradually becoming a hot and difficult point in the field of measurements of largeforgings size. Based on the strong noises, mass and localized characteristics of the3Dpoint clouds of large forgings size, utlizing3D point clouds meshless processing theory,the problem of accurate, rapid and reliable reconstruction methods of the feature curve oflarge forgings were researched indepth.
Firstly, based on anisotropic denoising theory, a new3D point clouds anisotropicdenoising model was estiblashed for large forgings3D data, using the differentialgeometric information of the sampled points. The shape and orientation of the denoisingkernel function were ajusted adaptivly. A new3D point clouds denoising alghrithm wasproposed for large forgings based on the new model. The strong noises are smoothed,meanwhile the feature feature of the forgings are preserved, laying the foundation for theaccurate reconstruction of the feature curve of large forgings.
Secondly, measure theory and estimation theory of discrete differential geometrywere combined together. The information similarity model was established toquantitativly describe the differential geometrical similarity between the the sampledpoints. The contract pairs were constructed under the princple of maximum informationsimilarity. The information similarity weighted quadric error matric was construced foreach sampled point based on the information similarity between the sampled point and itsneighbors. The optimal position of the contracted pair was solved by minmizing theweighted error matric, the cost of the contraction was evaluated by the minmum value ofthe weighted error matric. A3D point clouds meshless simplification algorithm wasproposed for larging forgings based on the concept of iteratively contracting the least costpairs, providing guarantees for the accurate and rapid structural curve reconstruction of large forgings.
Thirdly, a new3D point clouds registration measue was proposed based on kerneldensity estimation theory. The BFGS quasi-Newton optimization and simulated annealingalgorithm was combined together to search the maxmum point of the measure in varyingscaled manner. A robust variant scale3D point clouds registration algorithm was proposedbased on the principle, in order to solve the conflicts between accuracy and convergenceinterval of classical registration algorithms, laying the foundation for the integratedreconstruction of the feature curve of large forgings. Tensor decomposition theory andmulti-scale analysis theory were combined together. Multi-scaled tensor characteristicindex was constructed to describe the characteristics of the sampled points. Based on thecapability of the Multi-scaled tensor characteristic index in distinguishing the featurepoints, the minmum spanning forest algorithm was usd to connect the feature points andconstruct the featured polygonal lines. Furthermore, polygonal lines were smoothed bymoving least squares algorithm, and the fake feature points were projected to thesmoothed curves. In such way, the featured curves of large forgings were constructedreliably.
Finaly,3D measurement of the simulated forgings was undergone by the laserscanning3D measure platform. The experimental results reveals that the accuracy,rapidity and reliablity of the proposed methods.
引文
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