Surface fitting and representation by using 2D least squares method in CAD applications

Abstract EN

This paper presents a general method for automatic surface fitting from scattered range data and describes the implementation of three methods for fitting surfaces: linear, quadratic and cubic.

It uses a modified 2D least squares method to fitting, reconstructing and modeling several surfaces and statistical criteria to compare the three approaches.

The comparison is performed using a mathematically defined data as real data obtained from the proposed models.

The method can be used in a variety of applications such as reverse engineering, automatic generating of a CAD model, etc, and it has proven to be effective as demonstrated by a number of examples using real data from mathematical functions (sine, cosine, exponential and cubic).

By applying the proposed surface fitting model the standard deviation was found to be (0.04-0.26), (0.02-0.07) and (0.0-0.12) mm for linear, quadratic and cubic fitting models respectively.