期刊文献+

机械式反操纵负载模拟器的设计方法 被引量:2

Design Method of Mechanical Reverse Operation Simulator
下载PDF
导出
摘要 针对机械式反操纵负载模拟器加载精度低的问题,提出了提高其加载精度的设计方法,即采用虚位移原理法对机械式反操纵负载模拟器建立负载力矩模型,利用杆件角度的变化从负载力矩模型中分析得出杆件的合理范围.通过对负载力矩模型的负载曲线做逼近处理,达到对负载力矩模型进行重构的目的.提出了利用负载力矩模型杆件角度分析与蒙特卡罗相结合的方法来设计杆件,其优点在于可找寻同时满足多级加载梯度条件的杆件组,避免了传统方法的不足,即利用最大加载角度进行优化从而导致无法模拟真实加载情形及最终找寻到的是加载梯度少的杆件组.最后,利用仿真验证了优化结果. Due to the mechanical reverse operation simulator low accuracy problem,design method is proposed to improve the loading accuracy. According to the principle of virtual displacement method,the torque and inertial torque models of mechanical reverse operation simulator were built. They were handled by means of curve function fitting tool. The integration of mechanical angle variable method and Monte-Carlo was proposed to solve the design parameters optimization in the available mechanical bar ratio range. The number of multi-type gradient links can be available when the reduced variable is applied to the design parameters of the mechanical reverse operation simulator. The proposed method avoids searching for bars in maximal loading angle the traditional way used in the parameters optimization,which can not simulate actual condition and achieve multi-type gradient links. After testifying by the simulation,the results are applied to the design of the mechanical reverse operation simulator.
出处 《天津大学学报(自然科学与工程技术版)》 EI CAS CSCD 北大核心 2014年第9期803-810,共8页 Journal of Tianjin University:Science and Technology
基金 国家自然科学基金资助项目(51175011)
关键词 机械式反操纵负载模拟器 曲线逼近 多级加载梯度 仿真 mechanical reverse operation simulator curve function fitting tool multi-type gradient simulation
  • 相关文献

参考文献10

  • 1Nam Yoonsu, Lee Jinyoung, Hong Sung Kyung. Force control system design for aerodynamic load simula- tor EC]//IEEE Proceedings of the American Control Con- ference. Chicago, USA, 2000: 3043-3047. 被引量:1
  • 2曹彤,孙杏初,欧阳沁,郑时镜.舵机反操纵负载台设计[J].北京航空航天大学学报,2003,29(3):252-254. 被引量:8
  • 3王冰.基于ANSYS和ADAMS的舵机反操作力矩加载试验台的仿真分析与研究[J].军民两用技术与产品,2007(8):43-44. 被引量:3
  • 4曲秀全著..基于MATLAB/Simulink平面连杆机构的动态仿真[M].哈尔滨:哈尔滨工业大学出版社,2007:168.
  • 5Li Yaohang. An efficient Monte Carlo method for multi- objective sampling over parameter space [J]. Computers and Mathematics with Applications, 2012, 64(2) : 3542-3556. 被引量:1
  • 6Bastin F, Cirillo C, Toint P L. Application of an adap- tive Monte Carlo algorithm to mixed logit estimation [J]. Tramportation Research: Part B, 2006, 40(1) : 577- 593. 被引量:1
  • 7Wu Fangcai, Dantan Jean-Yves, Etienne A, et al. Im- proved algorithm for tolerance allocation based on Monte Carlo simulation and discrete optimization [J]. Computer &IndustrialEngineering, 2009, 56(4) : 1402-1413. 被引量:1
  • 8Marseguerra M, Zio E. Optimizing maintenance and repair policies via a combination of genetic algorithms and Monte Carlo simulation[J]. Reliability Engineering and System Safety, 2000, 68(1): 69-83. 被引量:1
  • 9Marseguerra M, Zio E, Podofillini L. Condition-based maintenance optimization by means of genetic algorithms and Monte Carlo simulation [J]. Reliability Engineering andSystem Safety, 2002, 77(2) : 151-166. 被引量:1
  • 10Liu Min, Maute K, Frangopol D M. Multi-objective design optimization of electrostatically actuated mi- crobeam resonators with and without parameter uncer- tainty [J]. Reliability Engineering and System Safety, 2007, 92(10): 1333-1343. 被引量:1

二级参考文献5

共引文献7

同被引文献22

引证文献2

二级引证文献18

相关作者

内容加载中请稍等...

相关机构

内容加载中请稍等...

相关主题

内容加载中请稍等...

浏览历史

内容加载中请稍等...
;
使用帮助 返回顶部