Reducing the sensitivity to 3D scanning noises in measurement of planar surfaces

降低平面测量中 3D 扫描噪声的敏感性

• 批准号: 520969-2017
• 负责人: Barari, Ahmad
• 金额: $ 1.82万
• 依托单位: University of Ontario Institute of Technology
• 依托单位国家: 加拿大
• 项目类别: Engage Grants Program
• 财政年份: 2017
• 资助国家: 加拿大
• 起止时间: 2017-01-01 至 2018-12-31
• 项目状态: 已结题
• 来源: https://www.nserc-crsng.gc.ca/ase-oro/Details-Detailles_eng.asp?id=639894
• 关键词: Reducing; sensitivity; 3D; scanning; noises

Coordinate metrology is the main inspection method for product or process control in various manufacturingsystems today. The accuracy and reliability of inspection directly affect the quality of products or processes, therate of failure, and the production waste. Recent developments in optical coordinate metrology allows fastcapturing of large amount of 3D data points from the surface of the measured objects which is highly desiredfor dynamic measurements in automated production lines. However, the accuracy of measurement data highlydepends on various sources of noises during the surface scanning process. The noisy points in the scannedpoint cloud increase the amount of uncertainty at different areas in the 3D point cloud, which affects therobustness of the measurement. Additional challenges are encountered when the texture of scanned surfaces arehighly reflective. As there is no prior knowledge of how the noise is distributed in the point cloud, the optimumdetermination of model parameters is often a difficult and challenging process. This project investigates anapproach to improve the reliability and accuracy of the measurement by determining the number and locationof surface measurement points. It aims to find a solution for the planar surfaces and flatness evaluation becausethe flat surfaces and patches are the most common geometric features in various manufacturing products.Bluewrist Inc. is a Canadian - based company focused on automated measurement and production qualitycontrol systems who primarily services the advanced manufacturing sectors. Bluewrist's main product includein-line dimensional measurement systems, robotic guidance system, and automation engine andcommunication software. This project allows Bluewirst to develop a more reliable platform for coordinatemetrology and 3D scanning that can be implemented in their automated coordinate metrology products andservices to its clients. This research will assist Bluewrist to develop customized methodologies to reduce thelevel of metrology uncertainty for various Canadian industrial sectors. It will also have a direct impact ontraining of highly qualified personnel who can become the leaders of Canada's future metrology industry.

坐标测量是当今各种制造系统中产品或过程控制的主要检测方法。检测的准确性和可靠性直接影响到产品或工序的质量、故障率和生产浪费。光学坐标测量的最新发展允许从被测物体的表面快速捕获大量的3D数据点，这对于自动化生产线中的动态测量是非常必要的。然而，测量数据的准确性在很大程度上取决于表面扫描过程中的各种噪声源.扫描点云中的噪声点增加了三维点云中不同区域的不确定性，影响了测量的鲁棒性。当被扫描表面的纹理是高反射性的时，会遇到额外的挑战。由于点云数据中噪声的分布没有先验知识，因此模型参数的最优确定往往是一个困难而具有挑战性的过程。本计画探讨一种方法，借由决定表面量测点的数量与位置，以提高量测的可靠性与准确度。平面和曲面片是各种制造产品中最常见的几何特征，其目的是为平面和平面度评估找到一种解决方案。是一家加拿大公司，主要服务于先进的制造业，专注于自动化测量和生产质量控制系统。蓝腕的主要产品包括在线尺寸测量系统、机器人导向系统、自动化引擎和通信软件。该项目使Bluebrist能够开发一个更可靠的坐标测量和3D扫描平台，可以在其自动坐标测量产品和服务中实施。这项研究将有助于Bluewrist开发定制的方法，以减少加拿大各工业部门的计量不确定性水平。这也将对培养高素质人才产生直接影响，这些人才将成为加拿大未来计量行业的领导者。