Journal of South China University of Technology(Natural Science Edition) ›› 2012, Vol. 40 ›› Issue (3): 137-142.

• Mechanical Engineering • Previous Articles     Next Articles

ATS-FNN-Based Modeling and Simulation for Compensation Prediction of FWP Machining Deformation

Deng Yao-hua  Liu Gui-xiong   

  1. School of Mechanical and Automotive Engineering,South China University of Technology,Guangzhou 510640,Guangdong,China
  • Received:2011-11-18 Revised:2011-12-22 Online:2012-03-25 Published:2012-02-01
  • Contact: 刘桂雄(1968-) ，男，教授，博士生导师，主要从事智能传感技术、现代检测技术与网络化控制研究． E-mail: megxliu@scut.edu.cn E-mail:dengyaohua@gdut.edu.cn
  • About author:邓耀华(1978-) ，男，在职博士生，广东工业大学讲师，主要从事加工过程智能建模研究．
  • Supported by:

    教育部新世纪优秀人才支持计划项目( NCET-08-0211) ; 粤港关键领域重点突破项目( 20080102-5)

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Abstract:

In order to meet the real-time requirements of the prediction model for deformation compensation of flexible workpiece path ( FWP) with complex factors,a ATS-FNN ( Adaptive TS Fuzzy Neural Network) -based modeling method for the compensation prediction of FWP machining deformation is proposed. In this method,the adaptive fuzzy clustering method is employed to obtain the antecedent fuzzy membership functions and fuzzy rule fitness of TS-FNN from historical machining data,and the steepest descent method is used as the learning algorithm of the consequent network to quickly calculate the parameters of connection weights. Simulated results indicate that,as compared with the standard TS-FNN,the ATS-FNN reduces a modeling time of 52.34% and a mean square error of the predicted compensation respectively by 36.50% or 33.34% in x or y direction.

Key words: flexible workpiece, machining deformation, compensation prediction, modeling, fuzzy neural network, fuzzy clustering

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