Research On Key Technology In Intelligent Position-arching Machining Of Super-large Components

With the development of industrial technology, the application range ofsuper-large components is more widely. Meanwhile, higher precision and lowermanufacturing costs of super-large components are demanded. Intelligentposition-arching machining is a novel method for super-large components, whichcan theoretically improve the processing efficiency and reduce the cost of thesuper-large components. But the study of this method is still at the initial stage, andthe processing efficiency and machining precision can’t meet the needs of thesuper-large components. Therefore, carrying out the research on key technology inintelligent position-arching machining of super-large components has great practicalsignificance.The pose detection of the super-large components is one of the key technologiesin intelligent position-arching machining of super-large components. Iterativematching technique is usually used to achieve the pose detection of the super-largecomponents at present, but this method is complex, cockamamie for super-largecomponents. In order to improve the efficiency and precision of the pose detection，a novel method to detect the pose of super-large components was proposed, whichwas based on the shape features of the workpiece. Firstly the fundamental of thismethod was elaborated, and the detection precision was analyzed based on MonteCarlo algorithm. Then the transfer method of measuring coordinate was given, andthe precision was analyzed theoretically. Finally one experiment was carried out tocheck the feasibility of pose detection of super-large components.The pose of machine tool need to be detected when it was moved to the nextposition and the detection precision of machine tool has great influence on themachining precision of super-large components. The traditional method wasimplemented by "three-point method", which was seriously affected byenvironmental and human factors, resulting in detection precision of machine toolpose was poor. In this thesis, one reference coordinate system was set on themachine tool to detect the pose of machine tool quickly and accurately. Accordingto the repeatability experiments of the reference coordinate system, feasibility ofthis method was first analyzed. Then the calibration method of the referencecoordinate system method was given, and this error mode of the calibration methodwas built. The feasibility of this detection method of machine tool was checked bycalibration experiments and pose detection experiments of machine tool at last.In order to analyze and predict the machining accuracy of intelligent position-arching machining of super-large components, The error model of this manufacturing method was built in this thesis firstly. Meanwhile the major errorfactors were analyzed, and the geometric positioning error of machine tool and themeasurement error of the coordinate points were specifically explained. Finally themachining accuracy prediction was conducted based on Monte Carlo algorithm.Based on the theoretical study above, machining experiments were carried outon a rectangular super-large component. Moreover, some experiments about usingcan carry out the geometric positioning error detection and compensation wereconducted to improve the geometric positioning accuracy of the movable parallelmachine tool. The experimental results showed that intelligent position-archingmachining of super-large components was high-precision and high-efficiency andthe prediction model of machining accuracy was reliable.