Paper Info
Title
Study On Evaluation Of Perpendicularity Errors With An Improved Particle Swarm Optimisation For Planar Lines
Abstract
According to characteristics of perpendicularity error evaluation of planar lines, an improved particle swarm optimisation (PSO) is proposed to evaluate the minimum zone error. The evolutional optimum model and the calculation process are introduced in detail. Compared with conventional optimum methods such as simplex search and Powell method, PSO can find the global optimal solution, and the precision of calculating result is very good. Compared to other intelligence computation algorithms such as genetic algorithm (GA), PSO is easier to carry out with fewer parameters to adjust. Then, the objective function calculation approaches for using the particle swarm optimisation algorithm to evaluate minimum zone error are formulated. Finally, the control experiment results evaluated by different method such as the least square, simplex search, Powell optimum methods and genetic algorithm (GA), indicate that the proposed method can provide better accuracy on perpendicularity error evaluation effectively, and is well suited for position error evaluation.
Year
DOI
Venue
2013
10.1504/IJMIC.2013.051934
INTERNATIONAL JOURNAL OF MODELLING IDENTIFICATION AND CONTROL
Keywords
Field
DocType
metrology, perpendicularity error, minimum zone solution, particle swarm optimisation algorithm
Least squares,Particle swarm optimization,Mathematical optimization,Metrology,Simplex,Planar,Mathematics,Genetic algorithm,Computation
Journal
Volume
Issue
ISSN
18
1
1746-6172
Citations 
PageRank 
References 
0
0.34
0
Authors
2
Name
Order
Citations
PageRank
Ke Zhang176.11
Sheng-Ze Wang211.17