Font Size: a A A

Research Of Particle Swarm Optimization In The Parameter Identification Technology For Parallel Double-joints Coordinate Measuring Machine

Posted on:2016-02-23Degree:MasterType:Thesis
Country:ChinaCandidate:W X ZhengFull Text:PDF
GTID:2392330470484771Subject:Instrumentation engineering
Abstract/Summary:PDF Full Text Request
Parallel double-joints coordinate measuring machine is one of the portable coordinate measuring instruments whose advantages include a wide measuring range, the flexible freedom, light-weight etc. The key problem is how to ensure the accuracy of measurement. And the main work of this paper focuses on how to improve its accuracy.The main achievements are shown as:(1) Analyzes the mechanical structure of the Parallel double-joints coordinate measuring machine. Introduce two kinds of methods to solve the circular grating centrifugal error, and the installation method of wheel hub.(2) Reference industrial robot kinematics modeling and flexible articulated coordinate measuring machine mathematical modeling to establish systematic error model and random error model of Parallel Double-joints Coordinate Measuring Machine by the modified D-H theory, and use the Simulink software to verify this model.(3) Analyzes the calculation process and parameters of particle swarm optimization algorithm. Related parameters is set according to the model of the Parallel Double-joints Coordinate Measuring Machine.(4) Using particle swarm optimization algorithm to calculate the related parameters of the Parallel Double-joints Coordinate Measuring Machine. Comparing with gauss Newton iterative method, analyzes the advantages of particle swarm optimization algorithm.
Keywords/Search Tags:Parallel Double-joints Coordinate Measuring Machine, Error model, Parameter Identification, Gauss-Newton iteration, Particle swarm optimization algorithm
PDF Full Text Request
Related items