期刊文献+

软轴摩擦力计算公式的结构参数优化设计 被引量:5

The structure parameter optimization design of soft shaft friction empirical formula
在线阅读 下载PDF
导出
摘要 通过最小二乘回归分析方法推导出软轴摩擦力计算公式,并运用粒子群算法对其进行修正.修正后的软轴摩擦力计算经验公式可以有很多方面的应用.本文运用遗传算法结合该经验公式及某些约束条件对软轴摩擦力大小进行优化,得出最小摩擦力出现时软轴的几何参数.结果表明:在限定极限弯曲挠度的条件下,出现软轴摩擦力极小值时的芯轴长度及弯曲半径均取在所规定的取值边界上,而芯轴直径随着极限弯曲挠度的增大而减小. Soft shaft friction empirical formula is deducted by least-squares regression analysis method, then it is corrected by particle swarm optimization. The corrected empirical formula for calculating the shaft friction can be applied in many aspects. For example, the friction force can be calculated by putting three numerical values of the shape parameters into the empirical formula. The article attempts to use the genetic algorithm combined with the empirical formula and some constraints on the soft shaft friction optimization, then it obtains the geometric parameters of soft shaft as the minimum friction appears. The results show that: under the condition of limited maximum bending deflection, the minimal value of soft shaft friction appears when core shaft length and bending radius are specified in the values on the border. But the spindle diameter decreases with the increase of the limit bending deflection.
作者 李健 张宝 徐敏 李尽力 LI Jian ZHANG Bao XU Min LI Jin-li(School of Mechanical Engineering, Guangxi University of Science and Technology, Liuzhou 545006, Chin)
出处 《广西科技大学学报》 2016年第3期21-25,共5页 Journal of Guangxi University of Science and Technology
基金 广西科学研究与技术开发计划项目(10100026)资助
关键词 软轴 摩擦力 经验公式 遗传算法 soft shaft friction empirical formula genetic algorithm
  • 相关文献

参考文献12

  • 1张宏,董磊,赵秀梅.基于软轴式随动控制的运煤车液压转向系统分析[J].工程设计学报,2015,22(1):89-94. 被引量:1
  • 2季有昌.推土机单手柄变速转向机构的设计与研究[J].机械设计,2014,31(12):65-71. 被引量:3
  • 3李健,张宝,徐敏,李尽力.基于LS和PSO的钢丝软轴摩擦力计算公式推导[J].机械设计与研究,2016,32(2):171-174. 被引量:2
  • 4BERRO A, MARIE-SAINTE S L, RUIZ-GAZEN A. Genetic Algorithms and Particle Swarm Optimization for Exploratory Projection Pursuit [ J ]. Annals of Mathematics and Artificial Intelligence, 2010,60 ( 1 ) : 153-178.
  • 5SHAHBAZI S, KARUNASEKERA S, HARWOOD A. Improving Performance in Delay/Disruption Tolerant Networks through Passive Relay Points [ J ]. Wireless Networks, 2012,18 ( 1 ) : 9-31.
  • 6吴小蝶,曾文波,廖嘉嘉,李顺利.遗传算法在UWB陷波天线设计中的应用[J].广西科技大学学报,2015,26(4):60-63. 被引量:3
  • 7QUIRANTE T, LEDOUX Y, SEBASTIAN P. Muhiobjective Optimization Including Design Robustness Objectives for the Embodiment Design of a Two-Stage Flash Evaporator [J ]. International Journal on Interactive Design and Manufacturing, 2012,6 ( 1 ) : 29-39.
  • 8BANSAL S K, SINHA B N, KHOSA R L. γ-Amino Butyric Acid Analogs as Novel Potent GABA-AT Inhibitors : Molecular Docking, Synthesis, and Biological Evaluation[J]. Medicinal Chemistry Research ,2013,22( 1 ) : 134-146.
  • 9VARUN A, VENKAIAH N. Simultaneous Optimization of WEDM Responses Using Grey Relational Analysis Coupled with Genetic Algorithm while Machining EN 353 [ J ].The International Journal of Advanced Manufacturing Technology, 2015,76 ( 1 ) : 675-690.
  • 10SANTOS M C, MACHADO A R, BARROZO M A S,et al. Multi-Objective Optimization of Cutting Conditions when Turning Aluminum Alloys (1350-O and 7075-T6 Grades) Using Genetic Algorithm [J]. The International Journal of Advanced Manufacturing Teehnology, 2015,76 (5) : 1123-1138.

二级参考文献49

共引文献8

同被引文献32

引证文献5

二级引证文献9

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