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An investigation is under way to develop a control system for an industrial process which uses a vision systems as a sensor. The research is aimed at the improvement of product quality in commercial injection molding system. A significant enhancement has been achieved in the level of application of visually based inspection techniques to component quality. The aim of the research has been the investigation, and employment, of inspection methods that use knowledge based machine vision. The application of such techniques in this context is comprehensive, extending from object oriented analysis, design and programming of the inspection program, to the application of rule based reasoning, to image interpretation, vision system diagnostics, component diagnostics and molding machine control. In this way, knowledge handling methods are exploited wherever they prove to be beneficial. The vision knowledge base contains information on the procedures required to achieve successful identification of component surface defects. A collection of image processing and pattern recognition algorithms are applied selectively. Once inspection of the component has been performed, defects are related to process variables which affect the quality of the component, and another knowledge base is used to effect a control action at the molding machine. Feedback from other machine sensor is also used to direct the control procedure. Results from the knowledge based vision inspection system are encouraging. They indicate that rapid and effective fault detection and analysis is feasible, as is the verification of system integrity.© (1997) COPYRIGHT SPIE--The International Society for Optical Engineering. Downloading of the abstract is permitted for personal use only. |
