Research On Geometric Analysis Algorithm And Visualization Technology Of Point Cloud Data

The dimension inspection of large workpieces is a key link to ensure the accurate manufacturing of products,and it directly reflects the processing accuracy of large workpieces.According to the traditional detection method,the external dimension detection of large workpieces is generally carried out by contacting a fixed-size mold and the workpiece to be measured.The traditional detection method is restricted by the measurement environment and the professional level of the measurement personnel,and the measurement accuracy and efficiency are low.With the continuous innovation of industrial product manufacturing technology,the output of large workpieces has increased sharply,resulting in traditional inspection methods that cannot meet the requirements of external dimension inspection.At the same time,in order to meet the needs of real-time feedback of the processing status of the measured workpiece,it is required to display the deviation between the measured workpiece and its theoretical model and the position of the deviation.In addition,it is necessary to accurately measure the size of specific parts of the workpiece.The past inspection methods can no longer meet the requirements of high-precision and high-efficiency inspections.Three-dimensional laser scanning technology has a wide range of applications in industrial inspection due to its high data collection efficiency,non-contact,and strong universal applicability.At present,the non-contact measurement method of scanning the workpiece with a laser scanner is usually used to collect point cloud data on the surface of the workpiece,and the point cloud data is analyzed and processed to detect the shape and size of a large workpiece.However,the accuracy and robustness of many common point cloud data analysis and processing methods in actual measurement have yet to be verified,and a complete set of analysis algorithms has not been formed.The decentralized application of existing point cloud data processing and analysis algorithms cannot meet new detection needs.Various point cloud analysis algorithms must be combined and applied to verify their practicability and explore suitable visualization methods.Various point cloud analysis algorithms must be combined to verify their practicability and explore suitable visualization methods.Therefore,this paper designs and develops a set of geometric analysis algorithms based on point cloud data.Through point cloud splicing,the complete point cloud data on the surface of the measured workpiece is obtained,and the processing deviation between the measured workpiece and the theoretical model is calculated through the registration of the point cloud and the model.Meet the requirements of feedback of the processing status of the tested workpiece.The point cloud data of a specific part of the measured workpiece is extracted through point cloud segmentation,and then the geometric quantity to be measured is calculated by shape fitting and compared with the model design value,so as to realize the detection of the shape and size.