Reverse engineering of compound surfaces using boundary detection method

Cho, Myeong-Woo; Sea, Tae-Il; Kim, Jae-Doe; Kwon, Oh-Sang

doi:10.1007/bf03185064

Cited by 6 publications

(1 citation statement)

References 10 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Plenty of solutions in the advanced and modern industry are being provided as far as designing and manufacturing are concerned (Youssef 2001, Yau and Chen 1997, Cho et al 2000. In modern designing, scanned digital data lead to the adoption of contour styling (Sarfraz et al 2001(Sarfraz et al , 2005a, which helps to guide visual acceptance after adopting some curve or surface approximation scheme (Dierckx 1992, Farin 1989, Piegl and tiller 1991.…”

Section: Introductionmentioning

confidence: 99%

Computer-aided reverse engineering using simulated evolution on NURBS

Sarfraz

2006

Virtual and Physical Prototyping

View full text Add to dashboard Cite

The current study is related to the issue of computer-aided reverse engineering. Although the proposed technique has been suggested and adopted for the image-based planar objects, it is extendable to the objects in three dimensions (3D) with some modifications. The objective of the present study is to provide a robust and automated solution and methodology for the applications of reverse engineering technology in manufacturing and other industries. By extracting nearly exact geometric data of the models, the key points (one may call them 'corner points') from the data are detected using an efficient technique. Then curve or surface models are fitted by using non-uniform rational Bsplines (NURBS). In curve or surface fitting problems, the selection of appropriate parameters, in order to obtain an optimized shape design, is a well-known problem. For large data, this problem needs to be dealt with by optimization algorithms avoiding possible local optima and at the same time reaching the desired solution in an iterative fashion. Many evolutionary optimization techniques including genetic algorithm and simulated annealing have been applied to the problem. This paper presents an application of an evolutionary heuristic technique known as 'simulated evolution' (SimE) to the curve and surface fitting problems using NURBS. NURBS have become the standard for representing curves and surfaces. This paper presents a method for approximating NURBS using digitized data. Instead of using the classical optimization approach to solve the problem, a new method based on SimE is developed. The shape parameters, in the description of NURBS, have been targeted to be optimized in a best possible way. The paper describes the mapping scheme of the problem to SimE followed by the proposed algorithm outlines with the interesting results obtained.

show abstract