A Study On Information Extraction Of Parts And Automatic Recognize For The Position And Orientation In Coordinate Measuring Systems

With the rapid development of manufacturing industry, especially the highly valued and being put in practice cosmically of Computer Integrated Manufacturing System, coordinate measuring machine (CMM) is becoming the major inspection equipment in quality control system of automatic production. Though CMM has two modes of automatic measurement: the programming mode and the self-learning mode,it does lie behind the requirement of automatic manufacturing industry and does limit the function applications of CMM in quality control. Therefore, the study on intelligent CMM is one of the key techniques for the development of manufacturing industry. Among the key techniques in intelligent CMM, the CAD/CMM interface technique and the automatic recognition for the position and orientation of parts are the most important key techniques. They are the precondition and foundation of other techniques in intelligent CMM system. The former can realize the automatic extraction of part features and inspection items based on the CAD design data files, which provide the necessary information such as inspection item, feature size and orientation dimension. The latter can recognize the posture, position and orientation by capturing the image of measured parts using CCD camera, which established the foundation for setting up part coordinate frame and programming the inspection path etc.This dissertation is subject to the project of"The Intelligent Techniques of CMM". At the same time, it is a component of"the development of measuring machine for parts outline", too. The goal of this thesis is to farther realize the intelligence of CMM for reducing operator's participation to the least extent through the study of the above two pivotal techniques. Surrounding how to realize the automatic extraction of parts information and the automatic recognition for the position and orientation, the major research and creative work of this thesis includes the following aspects:â… . The composing of intelligence CMM system is roundly reviewed and thoroughly analyzed. And the key techniques to realize the intelligence of CMM are elucidated deeply.â…¡. For the information extraction of part designed by Pro/Engineer, the automatic extraction application is developed based on the software Pro/Engineer and the development tools Pro/TOOLKIT.1. The Development mechanism and methods of Pro/TOOLKIT application areanalyzed thoroughly. The work modes of application and the setting of development environments are discussed detailed.2. The application to extract the relative information of extrude feature is researched with emphasis on the extraction work of geometry information and tolerance information.3. Based on the section shape, the revolution feature is classified into two kinds: the solid revolution feature and the empty revolution feature. And their information extraction applications are developed.â…¢. The automatic recognition system for the position and orientation of parts is researched deeply.1. The CCD camera is fixed on the Z axis of CMM, and the relation between CCD coordinate frame and CMM coordinate frame is established by using probe coordinate frame as"bridge". At the same time, the calibration method between CCD coordinate frame and probe coordinate frame is designed dexterously through taking full advantage of the precision movement of CMM and the nicer optics characteristic of white ceramic standard ball. By this calibration method, both the interior parameters of CCD and the coordinate frame relation of CCD and probe can be made certain in one calibration process.2. To realize intelligence, the automatic choosing arithmetic of image threshold is designed based on the improved Genetic Algorithm. In this method, the Greedy Genetic Algorithm and Otsu means are integrated. And the designed arithmetic can satisfy the real-time image processing system perfectly.3. The theory of moment invariants for the edge images is studied. And it is applied into the image matching of automatic recognition system for the position and orientation in a creative way. This image matching method is favorable to guarantee the real-time requirement because of the characteristics such as less restrict conditions, less calculation, matching rapidly and so on.4. Based on the ability of patter recognition and the characteristics such as self-adaptable learning, non-linear, strong fault tolerance capability and so on, the BP (Error Back Propagation) Neural Network is used as classifier. The moment invariants of virtual images of part are used to train the Neural Network. And the pose of measured part can be recognized by using the moment invariants of captured image as the input of trained Neural Network because of the matched virtual image representing the pose of part on the worktable.5. The position and orientation of parts in the image is recognized by calculating the edge moment of part image. And the automatic recognition function for the position and orientation of part in machine coordinate frame is realized through the coordinate transform between CCD coordinate frame and CMM coordinate frame.