1st International ICST Workshop on Artificial Intelligence in Grid Computing

Research Article

A Minimum Zone Method for Evaluating Flatness Errors Based on PSO Algorithm

  • @INPROCEEDINGS{10.1145/1577389.1577395,
        author={Ke Zhang and Kun Gao and Hui Zhang},
        title={A Minimum Zone Method for Evaluating Flatness Errors Based on PSO Algorithm},
        proceedings={1st International ICST Workshop on Artificial Intelligence in Grid Computing},
        publisher={ACM},
        proceedings_a={AIGC},
        year={2007},
        month={8},
        keywords={Metrology Flatness error Minimum zone solution PSO algorithm.Algorithms Measurement Performance Design.},
        doi={10.1145/1577389.1577395}
    }
    
  • Ke Zhang
    Kun Gao
    Hui Zhang
    Year: 2007
    A Minimum Zone Method for Evaluating Flatness Errors Based on PSO Algorithm
    AIGC
    ACM
    DOI: 10.1145/1577389.1577395
Ke Zhang1,*, Kun Gao2,*, Hui Zhang3,*
  • 1: Shanghai Institute of Technology 120 Caobao Road, 200235 Shanghai, P. R. China
  • 2: Computer Science and Information Technology College Zhejiang Wanli University No. 8 South Qianhu Road, China
  • 3: Suzhou Mingzhi Foundry Equipment Co., Ltd., SuZhou, P. R. China
*Contact email: zhangk2007@gmail.com, gaoyibo@gmail.com, zhang_hui@mingzhi-tech.com

Abstract

In this paper, based on the analysis of existent evaluation methods for flatness errors, an intelligent evaluation method is provided. The evolutional optimum model and the calculation process are introduced in detail. According to characteristics of flatness error evaluation, Particle Swarm Optimization (PSO) is proposed to evaluate the minimum zone error. Compared with conventional optimum methods such as simplex search and Powell method, it can find the global optimal solution, and the precision of calculating result is very good. Then, the objective function calculation approaches for using the PSO 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 GA, indicate that the proposed method does provide better accuracy on flatness error evaluation, and it has fast convergent speed as well as using computer easily and popularizing application easily.