计算机集成制造系统 ›› 2016, Vol. 22 ›› Issue (第4期): 1070-1078.DOI: 10.13196/j.cims.2016.04.021

• 产品创新开发技术 • 上一篇    下一篇

基于状态熵的多态制造系统可靠性分析

周丰旭1,李爱平1,李益1,谢楠2,刘雪梅1,徐立云1   

  1. 1.同济大学现代制造技术研究所
    2.同济大学中德工程学院
  • 出版日期:2016-04-30 发布日期:2016-04-30
  • 基金资助:
    国家高档数控机床与基础制造装备科技重大专项资助项目(2011ZX04015-022)。

Reliability analysis of multi-state manufacturing systems based on state entropy

  • Online:2016-04-30 Published:2016-04-30
  • Supported by:
    Project supported by the National Science and Technology Major Project,China(No.2011ZX04015-022).

摘要: 针对制造系统的状态多样性和传统可靠性分析问题的条件约束,研究了一种基于状态熵的多态制造系统可靠性分析方法。采用从元件到子系统、从子系统到系统的层级划分方法对多态制造系统进行性能分析,在信息熵理论的基础上建立了多态制造系统状态熵数学模型,提出通用发生函数与最大熵原理相结合的多态制造系统可靠性分析方法,给出了求解最大熵概率密度函数的步骤。通过勒让德转换和牛顿切线法,得出最大熵概率密度函数中的拉格朗日乘子并求出系统的可靠度,对多态制造系统的可靠性进行了探讨。结合实例分析,并与传统的可靠性分析方法做比较,验证了所建模型的合理性和所用方法的有效性。

关键词: 多态制造系统, 通用生成函数, 最大熵概率密度函数, 状态熵, 可靠性分析

Abstract: Aiming at the status diversity of manufacturing system and the condition restriction of traditional reliability analysis,a multi-state manufacturing system reliability analysis method based on state entropy was researched,which used hierarchy divided approach to analyze the multi-state manufacturing system performance.A multi-state manufacturing system entropy state mathematical model was established based on information entropy theory.The multi-state manufacturing system reliability analysis method by combining Universal Generating Function (UGF) with Maximum Entropy Principle (MEP) was proposed,and the steps to solve the maximum entropy probability density function was given.Through Legendre transformation and Newton tangent method,Lagrange multipliers in maximum entropy density function were obtained,and the availability of multi-state manufacturing system was discussed.A case was taken as an example and in comparison with the traditional reliability analysis method to verify the rationality and the effectiveness of the proposed model and the analysis method.

Key words: multi-state manufacturing system, universal generating function, maximum entropy density function, state entropy, reliability analysis

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