A low-rigidity workpiece assembly deformation prediction method based on point cloud data

Abstract

The invention belongs to the field of reverse finite element analysis, and relates to a low-rigidity workpiece assembly deformation prediction method based on point cloud data. The method includes: Firstly, adopting a three-dimensional laser scanner to scan a to-be-tested low-rigidity workpiece, obtaining point cloud data of surface information of the to-be-tested low-rigidity workpiece, and carrying out point cloud simplified filtering processing; Secondly, completing three-dimensional transformation of point cloud coordinates in a three-dimensional coordinate system, rotating a normal vectorof the point cloud to be perpendicular to an xy plane, enabling a straight line to be parallel to an x axis and enabling a boundary of the point cloud to be parallel to the x axis, and completing two-dimensional grid division by utilizing the xy plane coordinates; adopting a radius search method and a least square method to obtain a point cloud ordered representation point of the low-rigidity workpiece; And finally, forming a quadrilateral grid by taking every four representative points as a group, outputting a required grid format, and inputting the quadrilateral grid format into finite element analysis software for constraint and displacement loading to obtain the shape change of the assembled low-rigidity workpiece. The method has the characteristics of rapidness and accuracy, and theconnection assembly time and cost are effectively saved.

Description

technical field [0001] The invention belongs to the field of reverse finite element analysis, and relates to a method for predicting assembly deformation of low-rigidity parts based on point cloud data. Background technique [0002] During the assembly process of aerospace parts, due to errors such as component processing deformation, gaps will be generated at the assembly connection interface. Therefore, there will be a gap measurement step in the connection and assembly of aircraft parts, and the traditional assembly gap measurement method is inefficient, the measurement results are unstable, and the artificial influence is large. These traditional measurement methods are no longer applicable when assembly clearances are small and interiors are not accessible. If the assembly gap can be predicted before component assembly and the link of gap measurement can be omitted, it can save a lot of connection assembly time and cost. The present invention proposes a method for pre...

AI Technical Summary

Problems solved by technology

[0005] Purpose of the present invention: due to the flexible characteristics of a low-rigidity part, its measurement shape is usually different from its assembly shape, in order to solve the problem that the bonding gap caused by the difference between the two affects the quality of the connection and assembly of large aeronautical components, provide A method for predicting assembly deformation of low-rigidity parts based on point cloud data

Images