Direct Measurement from Scan Data with Adaptive Moving Least-Squares Surfaces under Controlled Spatial Dependency

在受控空间依赖性下利用自适应移动最小二乘曲面直接测量扫描数据

• 批准号: 1030347
• 负责人: Xiaoping Qian
• 金额: $ 35.05万
• 依托单位: Illinois Institute of Technology
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2010
• 资助国家: 美国
• 起止时间: 2010-09-01 至 2014-08-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1030347&HistoricalAwards=false
• 关键词: Direct; Measurement; Scan; Data; Adaptive

The research objective of this award is to apply the method of moving least-squares to obtain a faithful representation of as-measured surfaces, from which dimensional characteristics of both engineered artifacts and natural objects can be accurately extracted. A moving least-squares surface defines a continuous surface directly from a set of points, a canonical representation of data output from various three-dimensional scanning systems. The proposed approach is to adaptively vary kernel widths of Gaussian functions and to control spatial dependency of deviations between points and the moving least-squares surface. If successful, this research would lead to a paradigm shift in computational metrology, from current intermediate surface reconstruction with accuracy lost in translation to direct measurement from scan data. The research will positively impact a host of industries where three-dimensional scanning is used such as aerospace, automobile, mass customization and biomedical applications. This research would shorten inspection cycles, reduce defect rates, and improve product quality, thus broaden the usage of three-dimensional scanning technologies in manufacturing systems, and thereby strengthen domestic manufacturer's competitiveness. The enhanced accuracy in scan data processing would also benefit biomedical industry and lead to enhanced biomedical imaging and diagnosis. Through its integrated research, education and outreach activities, this project will provide advanced knowledge in computational metrology for students from high schools to graduate schools and will increase domestic students' interest in science and engineering and therefore strengthen our competitiveness in the global workforce.

该奖项的研究目标是应用移动最小二乘法获得测量表面的忠实表示，从中可以准确提取工程文物和自然物体的尺寸特征。移动最小二乘曲面直接从一组点定义连续曲面，这是从各种三维扫描系统输出的数据的规范表示。所提出的方法是自适应地改变高斯函数的核宽度，并控制点与移动最小二乘曲面之间的偏差的空间依赖性。如果成功的话，这项研究将导致计算计量学的范式转变，从目前的中间表面重建与准确性损失的翻译，直接测量扫描数据。该研究将对许多使用三维扫描的行业产生积极影响，如航空航天，汽车，大规模定制和生物医学应用。本研究将缩短检测周期，降低不良率，提升产品品质，进而扩大三维扫描技术在制造系统中的应用，进而提升国内制造业的竞争力。提高扫描数据处理的准确性也将有利于生物医学工业，并导致增强的生物医学成像和诊断。通过其综合研究、教育和外联活动，该项目将为从高中到研究生院的学生提供先进的计算计量学知识，并将提高国内学生对科学和工程的兴趣，从而加强我们在全球劳动力中的竞争力。