SGER: Flexible Active Computer Integrated Inspection Based on Computer-Aided Design Models

SGER：基于计算机辅助设计模型的柔性主动计算机集成检测

• 批准号: 9319208
• 负责人: Michael Marefat
• 金额: $ 2.52万
• 依托单位: University of Arizona
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 1993
• 资助国家: 美国
• 起止时间: 1993-09-01 至 1995-08-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=9319208&HistoricalAwards=false
• 关键词: SGER; Flexible; Active; Computer; Integrated

9319208 Marefat The objectives of this project are to develop a new research program involving multi disciplinary work in active machine vision, flexible manufacturing, and artificial intelligence, which address CAD problems in automated visual inspection of manufactured (particularly machined) components based on their (CAD) design models. This research addresses two facets which are both important for success in this new research direction. The first facet is concerned with automated intelligent generation of inspection plans. This facet, which may be done off line, essentially constructs the inspection strategy. The second facet deals with the lower level methods for effective execution of the generated inspection plan together with sensors and other resources. In order to achieve the integrated intelligent inspection goals, the project addresses several interrelated problems. These problems include: (i) developing hierarchical representation mechanisms to effectively capture the knowledge about geometric entities, their relationships, sensors, and plans (ii) reasoning mechanisms to determine the different attributes of the different features of object to be inspected, and the alternative strategies which can be used for inspection of each attribute, (iii) strategies for placement and viewing angles of cameras, and for determining the visible entities in each configuration, and (iv) optimization of the constructed plan. An effective solution to this problem is clearly very important not only from the automation point of view, but also in order to effectively gather and use sensor information to overcome the volume and complexity of the needed data pro cessing for adequate performance. The requested support will be used for investigations to achieve further results, and to develop a limited prototype system. The ultimate goals are to demonstrate the developed limited prototype to industrial clients to stimulate their interest and involvement, and also to document the research results in professional publications.

小行星9319208 该项目的目标是开发一个新的研究计划，涉及主动机器视觉，柔性制造和人工智能的多学科工作，解决基于其（CAD）设计模型的制造（特别是机加工）部件自动视觉检测中的CAD问题。 这项研究解决了两个方面，这两个方面都是重要的成功，在这个新的研究方向。 第一个方面涉及检查计划的自动智能生成。 这个方面，可以离线完成，基本上构建了检查策略。 第二个方面涉及有效执行生成的检查计划以及传感器和其他资源的较低级别方法。 为了实现综合智能检测的目标，该项目解决了几个相互关联的问题。 这些问题包括：（i）开发分层表示机制以有效地捕获关于几何实体、它们的关系、传感器和计划的知识（ii）推理机制以确定待检查对象的不同特征的不同属性，以及可用于检查每个属性的替代策略，（iii）用于相机的放置和视角的策略，并且用于确定每个配置中的可见实体;以及（iv）优化所构造的计划。 这个问题的有效解决方案显然非常重要，不仅从自动化的角度来看，而且为了有效地收集和使用传感器信息，以克服所需数据处理的数量和复杂性，以获得足够的性能。 所要求的支助将用于调查，以取得进一步成果，并开发一个有限的原型系统。 最终目标是向工业客户展示开发的有限原型，以激发他们的兴趣和参与，并将研究结果记录在专业出版物中。