A fast calculation method of workpiece allowance based on 3D measurement point cloud data

Abstract

The present invention provides a method for quickly obtaining workpiece margin based on three-dimensional measurement point cloud data, which includes the following steps: use a scanner to scan the workpiece to obtain point cloud data; filter and denoise the point cloud data, and use the kd-tree method to obtain Take the normal line of the point cloud; import the theoretical model of the workpiece, and use the method of combining NDT and ICP to complete the registration of the 3D point cloud data after filtering and denoising with the theoretical model; use the octree data structure to space the point cloud data Divide, build a hash table, quickly encode the triangular facets of the divided space, and complete the preprocessing of the point cloud data; reduce the dimension of the preprocessed point cloud data, and filter out the triangular faces that are irrelevant to the calculation of the margin of the points to be selected slices; applying vector products and cross products to the remaining triangular faces to quickly obtain the margin and judge the validity; the beneficial effects provided by the present invention are: the large-scale point cloud is encoded through the space division of the octree and the hash table, The search efficiency is effectively improved, and the quick calculation of the workpiece allowance is realized.

Description

technical field [0001] The invention relates to the field of three-dimensional reconstruction, in particular to a method for quickly obtaining workpiece margin based on three-dimensional measurement point cloud data. Background technique [0002] With the increasing of people's individual needs and the development of digital design and manufacturing technology, the precision requirements of parts processing and manufacturing and assembly technology have posed unprecedented challenges to its error detection technology. The traditional two-dimensional detection method is time-consuming and labor-intensive to detect the shape, position and size, and it is difficult to achieve high-precision detection for some complex curved surface shapes. Its detection accuracy and efficiency have been difficult to meet the detection standards and requirements of modern industrial manufacturing technology for various parts. Modern digital inspection technology based on three-dimensional CAD mo...

AI Technical Summary

Problems solved by technology

In this kind of problem, the general algorithm is to screen all the triangular faces. When the required margin is large, it is easy to have problems such as low calculation efficiency and long time. After analysis, it can be found that the data is not pre-prepared in the general algorithm. processing, causing the filtering process to be too slow

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