欢迎访问机床与液压官方网站!

咨询热线:020-32385312 32385313 RSS EMAIL-ALERT
基于改进灰色关联度的液压系统可靠性模型优选方法
作者:
作者单位:

作者简介:

通讯作者:

中图分类号:

基金项目:

河南省高等学校重点科研项目(17B460007)


Reliability Model Selection Method of Hydraulic System Based on Improved Grey Correlation
Author:
Affiliation:

Fund Project:

  • 摘要
  • |
  • 图/表
  • |
  • 访问统计
  • |
  • 参考文献
  • |
  • 相似文献
  • |
  • 引证文献
  • |
  • 资源附件
  • |
  • 文章评论
    摘要:

    针对目前以假设检验等方法进行模型优选区分度和准确性不高的问题,提出了基于斜率相似和中值相近的灰色关联度模型优选方法,研究了该优选方法的算法。根据采集的数控磨床液压系统的可靠性数据,分别用5种概率密度函数对液压系统进行了建模,并利用所提模型优选方法对5种分布模型进行了拟合优度检验,结果显示液压系统最适合于伽马分布。与相关系数法、传统灰色关联度法、K-S检验等方法进行模型优选相比,基于改进灰色关联度的模型优选方法的区分度分别提高了86.42%、67.27%、2.59%,且准确性很高,优选效果良好。所述的模型优选方法可以用于可靠性模型的优选,也可以为其他曲线拟合的优选提供参考。

    Abstract:

    To solve the problem of low discrimination and low accuracy of reliability model selection of assumed test methods at present, one grey correlation model optimal selection method based on similar slope and closer median is put forward and the algorithm is studied. The reliability models of hydraulic system were established by 5 probability density functions based on the collected reliability data of hydraulic system of the computer numercial control (CNC) grinder. The proposed reliability model selection was carried out for fitting and optimal test of five different kinds of distribution models. The result showes that gamma distribution is most suitable for the hydraulic system. The discrimination is enhanced by 86.42%, 67.27% and 2.59% by the proposed model selection method compared by the correlation coefficient method, common grey correlation and Kolmogorov-Smirnov (K-S) method. The accuracy is very high and the model selection effect is good. The proposed method can be used to select the best reliability model in reliability design and it is also the reference to other model selection of curve fitting.

    参考文献
    相似文献
    引证文献
引用本文

刘勇军,杨勇,张艳山.基于改进灰色关联度的液压系统可靠性模型优选方法[J].机床与液压,2018,46(1):168-172.
. Reliability Model Selection Method of Hydraulic System Based on Improved Grey Correlation[J]. Machine Tool & Hydraulics,2018,46(1):168-172

复制
分享
文章指标
  • 点击次数:
  • 下载次数:
  • HTML阅读次数:
  • 引用次数:
历史
  • 收稿日期:
  • 最后修改日期:
  • 录用日期:
  • 在线发布日期: 2018-04-16
  • 出版日期: