Earticle

초록

영어

With the fast advances of sensing technologies in the past decade, a significant amount of discrete point data has been obtained. Some of these points are of poor quality because of measurement uncertainty at the geometric discontinuity of mechanical parts. In this paper, a particle swarm algorithm is developed for optimally-constrained multiple-line fitting of discrete data points. It contains two important technical components: a) constrained least-squares fitting of multiple lines, b) particle swarm search for optimal corner/edge points. The algorithm is applied to two-dimensional and three-dimensional cases. Numerical experiments indicate the effectiveness and high accuracy of the proposed approach, compared to the conventional method. It can be used for the accurate determination of sharp edges or corners based on discrete data points measured in high-precision inspection and manufacturing.

목차

Abstract
 1. Introduction
 2. Constrained Least-squares Fitting of Multiple Lines
  2.1. Two-Dimension Case
  2.2. Three-dimension Case
 3. Particle Swarm Optimization for Exact Location of Corner
  3.1. Two-dimension Fitness
  3.2. Three-dimension Fitness
 4. Experimental Results and Discussion
 5. Conclusions
 References

키워드

저자

• Xuefei Shi [ School of Automation and Electrical Engineering, Beijing University of Science & Technology, Beijing, P.R. China ]

참고문헌

발행기관

간행물

표지보기 관심저널 등록

• 간행물명

  International Journal of Hybrid Information Technology

• 간기

  격월간

• pISSN

  1738-9968

• 수록기간

  2008~2016

• 십진분류

  KDC 505 DDC 605