Research On Measuring Pointcloud Data Processing Algorithm For Ring Forgings

Ring forgings are important parts of major mechanical equipment and are important bearing units in aero-engines.In single-unit aero-engine forgings,ring forgings are high-precision parts with a large proportion.In order to ensure the processing quality,the shape data and structure of the ring forgings are usually analyzed by laser-measured ring forging point cloud data.Due to the large volume of the ring forgings,complete ring forging data cannot be obtained in one scan,so multiple scans are needed to obtain the complete ring forging data.At the same time,the amount of data obtained by scanning is huge.In order to further reconstruct the surface and ensure the ring forging data can be processed quickly and efficiently,the complete model data after stitching is needed to be reduced.Therefore,the algorithms of stitching and reduction of the scanning data are studied.The specific research contents are as follows:Firstly,in order to obtain the complete point cloud model data of the three-dimensional(3D)ring forging,each two-dimensional(2D)point cloud data set scanned by the scanner needs to be stitched to obtain the complete radial section line data.Through the Beetle Antennae Search Algorithm(BASA),the repeated regions of the point cloud rough stitching are obtained,and then the point cloud boundary extraction algorithm,the two-dimensional analytical tensor voting algorithm and the logarithmic property are used to find three pairs of corresponding point pair.The complete radial cross section line data can be obtained by calculating the rotation and translation parameters according to the three pairs of corresponding point pairs.Secondly,the amount of data obtained by scanning is huge,which is not conducive to subsequent data processing.The paper proposes an improved Quadratic Error Metric(QEM)point cloud data reduction algorithm based on Artificial Immune Algorithm(AIA).The original point cloud model is grid-divided.The points in each grid are regarded as the initial antibodies.According to the QEM algorithm,the cost function of the initial antibody is calculated.The volume-based and minimum cost function derived from the QEM algorithm and its optimal solution are used as antigens.The specific response of antigens and antibodies in the immune system is used to find the points to be retained,and then all the grids are circulated to obtain the final reduced point cloud data.Finally,taking the point cloud data of ring forgings in the laboratory as the experimental subject.The 2D point cloud data obtained by the laboratory scanning is processed according to the algorithms proposed in this paper.The point cloud data is stitched and reduced according to the algorithm in this paper,and the experimental results are compared with the classical algorithms.The experimental results are analyzed according to the size parameters of the ring forgings.It is proved that the proposed stitching and reduction algorithms can effectively process the point cloud data.