Reliability evaluation method and algorithm for electromechanical product

被引:0
作者
刘勇军 [1 ]
范晋伟 [1 ]
李云 [1 ]
机构
[1] College of Electromechanical Engineering and Applied Electronics Technology, Beijing University of Technology
基金
国家自然科学基金重大项目; 中国国家自然科学基金;
关键词
reliability evaluation; mean time between failures; probability density function; electromechanical product;
D O I
暂无
中图分类号
TB114.3 [可靠性理论];
学科分类号
1201 ;
摘要
The reliability of electromechanical product is usually determined by the fault number and working time traditionally. The shortcoming of this method is that the product must be in service. To design and enhance the reliability of the electromechanical product, the reliability evaluation method must be feasible and correct. Reliability evaluation method and algorithm were proposed. The reliability of product can be calculated by the reliability of subsystems which can be gained by experiment or historical data. The reliability of the machining center was evaluated by the method and algorithm as one example. The calculation result shows that the solution accuracy of mean time between failures is 97.4% calculated by the method proposed in this article compared by the traditional method. The method and algorithm can be used to evaluate the reliability of electromechanical product before it is in service.
引用
收藏
页码:3753 / 3761
页数:9
相关论文
共 11 条
  • [1] Real-time reliability evaluation based on damaged measurement degradation data[J]. 王小林,蒋平,郭波,程志君. Journal of Central South University. 2012(11)
  • [2] Reliability Sensitivity-based Correlation Coefficient Calculation in Structural Reliability Analysis[J]. YANG Zhou,ZHANG Yimin*,ZHANG Xufang,and HUANG Xianzhen School of Mechanical Engineering & Automation,Northeastern University,Shenyang 110819,China. Chinese Journal of Mechanical Engineering. 2012(03)
  • [3] Weighted linear least squares estimation of diffusion MRI parameters: Strengths, limitations, and pitfalls[J] . Jelle Veraart,Jan Sijbers,Stefan Sunaert,Alexander Leemans,Ben Jeurissen. Neuroimage . 2013
  • [4] Reliability prediction for evolutionary product in the conceptual design phase using neural network-based fuzzy synthetic assessment
    Liu, Yu
    Huang, Hong-Zhong
    Ling, Dan
    [J]. INTERNATIONAL JOURNAL OF SYSTEMS SCIENCE, 2013, 44 (03) : 545 - 555
  • [5] On the origin of logarithmic-normal distributions: An analytical derivation, and its application to nucleation and growth processes[J] . Ralf B. Bergmann,Andreas Bill. Journal of Crystal Growth . 2008 (13)
  • [6] Assessment of the tool post reliability of a high-stiffness turning machine
    Lee, Seungwoo
    Han, Seungwoo
    Lee, Husang
    [J]. JOURNAL OF MECHANICAL SCIENCE AND TECHNOLOGY, 2007, 21 (08) : 1244 - 1252
  • [7] Control charts for monitoring field failure data
    Batson, Robert G.
    Jeong, Yoonseok
    Fonseca, Daniel J.
    Ray, Paul S.
    [J]. QUALITY AND RELIABILITY ENGINEERING INTERNATIONAL, 2006, 22 (07) : 733 - 755
  • [8] A revisit to block and recursive least squares for parameter estimation
    Jiang, J
    Zhang, YM
    [J]. COMPUTERS & ELECTRICAL ENGINEERING, 2004, 30 (05) : 403 - 416
  • [9] Optimal replacement policies determined using arithmetico-geometric processes
    Francis, LKN
    [J]. ENGINEERING OPTIMIZATION, 2001, 33 (04) : 473 - 484
  • [10] Reliability evaluation and selection of rolling element bearings
    Sehgal, R
    Gandhi, OP
    Angra, S
    [J]. RELIABILITY ENGINEERING & SYSTEM SAFETY, 2000, 68 (01) : 39 - 52