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.