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.