中国机械工程 ›› 2015, Vol. 26 ›› Issue (13): 1772-1775,1782.

• 机械基础工程 • 上一篇    下一篇

高速主轴有限元模型热学参数自适应辨识方法

王书亭1;刘俊龙1;刘涛1;谭波1;苟卫东2   

  1. 1.华中科技大学,武汉,430074
    2.青海华鼎实业股份有限公司,西宁,810018
  • 出版日期:2015-07-10 发布日期:2015-07-08
  • 基金资助:
    国家科技重大专项(2013ZX04005-011);青海省高新技术产业化促进计划资助项目(2012-G-Q06A)

Adaptive Parameter Identification Method for Thermal Finite Element Model of High-speed Spindle

Wang Shuting1;Liu Junlong1;Liu Tao1;Tan Bo1;Gou Weidong2   

  1. 1.Huazhong University of Science and Technology,Wuhan,430074
    2.Qinghai Huading Industries Co. Ltd.,Xining,810018
  • Online:2015-07-10 Published:2015-07-08
  • Supported by:
    National Science and Technology Major Project ( No. 2013ZX04005-011)

摘要:

高速加工中心高速主轴是一种复杂的力-热耦合系统,针对其数学模型边界条件难以确定这一难题,提出了一种在少量试验数据组的基础上推定有限元模型热学边界条件的方法。该方法应用最小二乘支持向量回归对样本参数进行辨识,结合遗传算法,实现了高速主轴有限元模型热学参数自适应辨识。结合HMC-80高速高速主轴进行了实验应用,验证了该方法的有效性。

关键词: 高速主轴, 热学参数, 自适应辨识, 支持向量机, 遗传算法

Abstract:

High-speed spindle worked in the state of thermo-mechanical coupling, the thermal characteristics were extremely difficult due to their dependence on different influences.The desired calculation accuracy of joints was the bottleneck of high-speed spindle design and performance prediction. A new method was proposed based on least squares SVM and genetic algorithm to automatically find the optimal thermal characteristics in spindle.On the basis of little test data, the thermal boundary parameters for FEM model could be accepted adaptively. Resultantly, the validity of presented method was validated by experimental calibration with a high-speed spindle of HMC-80 machine tool.

Key words:  high-speed spindle;thermal parameter, adaptive identification;support vector machine(SVM);genetic algorithm

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