Research of Self-learning of Plate Deformation Resistance based on Genetic Algorithm

被引:0
作者
He, Chunyu [1 ]
Jiao, Zhijie [1 ]
Wu, Di [1 ]
机构
[1] Northeastern Univ, State Key Lab Rolling & Automat, Shenyang 110004, Peoples R China
来源
MATERIALS PROCESSING TECHNOLOGIES, PTS 1 AND 2 | 2011年 / 154-155卷
关键词
plate; genetic algorithm; deformation resistance; self-learning; NEURAL-NETWORK; FLOW-STRESS; HOT DEFORMATION; MODEL; PREDICTION;
D O I
10.4028/www.scientific.net/AMR.154-155.260
中图分类号
T [工业技术];
学科分类号
08 ;
摘要
The model parameters value of deformation resistance determines the prediction accuracy of rolling force model during the plate rolling. According to the influencing factors analysis of rolling force calculation error, the genetic algorithm was introduced into the self-learning method of deformation resistance, and searches the optimal value of deformation resistance on the basic of space exploration and optimization ability of genetic algorithm. The decision variable selection, the coding and decoding, the fitness evaluation and the terminal conditions process were implemented during development process of self-learning system. The results show that the optimization speed and accuracy can meet production requirement.
引用
收藏
页码:260 / 264
页数:5
相关论文
共 8 条
  • [1] Development of constitutive equations for modelling of hot rolling
    Davenport, SB
    Silk, NJ
    Sparks, CN
    Sellars, CM
    [J]. MATERIALS SCIENCE AND TECHNOLOGY, 2000, 16 (05) : 539 - 546
  • [2] Dzubinsky M, 2003, METALURGIJA, V42, P179
  • [3] TOWARDS STRUCTURAL OPTIMIZATION VIA THE GENETIC ALGORITHM
    JENKINS, WM
    [J]. COMPUTERS & STRUCTURES, 1991, 40 (05) : 1321 - 1327
  • [4] A precision on-line model for the prediction of roll force and roll power in hot-strip rolling
    Kwak, WJ
    Kim, YH
    Lee, JH
    Hwang, SM
    [J]. METALLURGICAL AND MATERIALS TRANSACTIONS A-PHYSICAL METALLURGY AND MATERIALS SCIENCE, 2002, 33 (10): : 3255 - 3272
  • [5] Phaniraj MP, 2003, J MATER PROCESS TECH, V141, P219, DOI [10.1016/S0924-0136(02)01123-8, 10.1016/50924-0136(02)01123-8]
  • [6] NEURAL-NETWORK APPROACH TO FLOW-STRESS EVALUATION IN HOT DEFORMATION
    RAO, KP
    PRASAD, YKDV
    [J]. JOURNAL OF MATERIALS PROCESSING TECHNOLOGY, 1995, 53 (3-4) : 552 - 566
  • [7] A mathematical model for evolution of flow stress during hot deformation
    Serajzadeh, S
    [J]. MATERIALS LETTERS, 2005, 59 (26) : 3319 - 3324
  • [8] A study on genetic algorithm to select architecture of a optimal neural network in the hot rolling process
    Son, JS
    Lee, DM
    Kim, IS
    Choi, SK
    [J]. JOURNAL OF MATERIALS PROCESSING TECHNOLOGY, 2004, 153 : 643 - 648