MRI: Acquisition of a Laser Sensor, Computer Workstations and a 3D SynthaGram Monitor for Research in Virtual Engineering

该补助金为密歇根大学-迪尔伯恩（UM-D）的多学科制造相关研究提供支持，用于购买LDI CMM激光扫描探针套件、六个HP高端双处理器工作站集群和40“裸眼3D显示器（SynthaGram 404）。所要求的仪器将构成一个新的虚拟工程实验室的基本基础设施，并将支持正在进行的虚拟工程研究活动，包括精确测量或获取制造零件、表面质量检查和损坏零件的重新设计、模拟断裂和损坏、分析制造过程、智能工程诊断和基于视觉的检查或识别。这些研究的主要目标是开发创新算法，通过有效利用极其强大的传感器、计算机和可视化设备，满足制造业社会对高精度和自动化日益增长的需求。正在进行的研究活动的成果将导致：1）在用安装在坐标测量机（CMM）上的激光传感器取代接触式测头方面取得潜在的突破; 2）用于金属板成形的虚拟表面质量评估系统; 3）用于破损零件的翻新和再工程系统; 4）用于检测和识别的智能视觉系统;（5）工程诊断中的模糊学习。正在进行的研究也将有助于模拟焊料合金的疲劳寿命，并通过所需的计算机和可视化设备了解金属成形中从局部颈缩到断裂的变形行为。所要求的仪器将大大加强在UM-D，一个非博士研究基础设施。此外，我们亦会透过学生设计项目及研究训练，大幅提升澳门大学-澳门理工学院的教育品质。社区外展将激发高中生对科学和工程的兴趣，并扩大代表性不足的黑人少数民族和女性学生在迪尔伯恩和底特律社区的参与。

This grant provides support for the acquisition of a LDI CMM laser scanning probe kit, a cluster of six HP high-end dual-processor workstations and a 40'' glasses-free 3D monitor (SynthaGram 404) for multidisciplinary manufacturing-related research at the University of Michigan - Dearborn (UM-D). The requested instruments will form a fundamental infrastructure of a new virtual engineering laboratory, and will support ongoing research activities in virtual engineering, including accurate measurement or acquisition of manufactured parts, surface quality inspection and reengineering of broken parts, simulation of fracture and damage, analysis of manufacturing processes, intelligent engineering diagnosis and vision-based inspection or recognition. The main objective of these studies is to develop innovative algorithms for meeting the manufacturing society's growing demands for high accuracy and automation by making effective use of the extremely powerful sensor, computers and visualization device to be acquired. The outcome of the ongoing research activities will lead to: 1) a potential breakthrough in replacing touch probes with laser sensors mounted to coordinate measurement machines (CMMs); 2) a virtual surface quality evaluation system for sheet metal forming; 3) a refurbishing and reengineering system for broken parts; 4) an intelligent vision-based system for inspection and recognition; and 5) fuzzy learning for engineering diagnosis. The ongoing research will also contribute to the modeling of fatigue life of solder alloys and the understanding of deformation behavior from localized necking to fracture in metal forming by means of the requested computers and visualization device. The requested instruments will substantially strengthen the research infrastructure at UM-D, a non-Ph.D. granting institute, and will also significantly improve the education quality at UM-D through student design projects and research training. The community outreaching will inspire high-school students' interest in science and engineering, and broaden the participation of underrepresented black minority and female students in Dearborn and Detroit communities.