Research About Geometry-Based Measure Of Images For The Mechanical Part

It is real-time, in-machine and online measurement method that satisfys requirements on high-speed, precision, and quality. Machine vision (MV) extracts information from images of objectives for detecting, measuring and controlling. In the last two decades, it is wildly applied in high-end manufacturing equipments and production lines, for its advantages of non-contact, high speed, good stability, and high accuracy. Image processing is not only the core of MV and a hot topic in recent researches, but also is a bottleneck of applications in advanced manufacturing field. The bottleneck reflects on the lack of image processing solution for a special object. So, image measure for special solutions to mechanical parts'image is researched in this dissertation.The dissertation mainly includes:1. Current online MV-based inspection methods for the mechanical product are analyzed. New concepts and descriptors based on image structural dimensions are proposed. Firstly, factors that MV did not satisfy online inspection requirements are summarized to a result of poor reasonable image descriptions for mechanical parts'images. Secondly, mechanical parts and their digital images are consistency mapping. Thirdly, a theory model for space set of primitives in an image is proposed to elaborate geometrical features based on Topology.2. Incomplete and nonlinear characteristics of a mechanical part image are analyzed. Nonlinear factors in a MV system affect its applications in measurement. In the dissertation, new methods based on measure theory are used to reconstruct image primitives. They combine both image primitive's reconstruction concept in morphology, and power law and box dimension computing method in fractal geometry.3. A measurement law of similar objects'images with irregular shape is found from the research of both Hausdorff measurement and dimension theory in fractal geometry, to describe a structure primitive'space. Becacuse of the complexity of mechanical parts'images, the efficiency and rationality of image segmentation is correlated with both image analysis and image understanding. The correlation is showed by extracting image features and regions of interest. Topological set space segmentation and reconstruction theory, as well as Hausdorff measurement theory, are used to solve measurement problems for complex and similar contours, with a method of "Perimeter+Area" to structure primitives' space.4. A problem to extract geometric feature from images' feature space directly is difficult because of nonlinearity, which is solved by image feature space conversion with signal dimension reduction technology.5. A reconfigurable software based on machine vision for manufacturing is developed and several online MV inspection systems are designed.The above researches have been successfully applied to finish online inspections for several manufacturing processes The applications help the manufacturers to improve production efficiency and control product quality of the production process. Certainly, more efforts are need for study of image geometrical shape. At last, the dissertation proposes the lines of future work.