基于马尔可夫过程和通用生成函数的制造系统可靠性分析  

Reliability analysis of manufacturing system based on Markov process and universal generation function

作　　者：胡健 周金宇 庄百亮 HU Jian;ZHOU Jinyu;ZHUANG Bailiang(College of Mechanical Engineering,Jiangsu Institute of Technology,Changzhou 213001,CHN;College of Mechanical and Electrical Engineering,Jinling University of Technology,Nanjing 211169,GHN;Jiangsu Institution,China Academy of Mechinery Science&Technology,Changzhou 213001,CHN)

机构地区：[1]江苏理工学院机械工程学院,江苏常州213001 [2]金陵科技学院机电工程学院,江苏南京211169 [3]机械科学研究总院江苏分院有限公司,江苏常州213001

出　　处：《制造技术与机床》2020年第11期33-39,共7页Manufacturing Technology & Machine Tool

基　　金：国家科技重大专项(2018ZX04026001-008);国家自然科学基金(51275221);江苏省高校自然科学研究重大项目(16KJA460002)。

摘　　要：利用传统的可靠性分析方法求解复杂多状态系统问题时,往往会由于系统状态数增加,引起计算成本高、精度低等问题。针对这一情况,运用了一种基于马尔可夫随机过程方法和通用生成函数(universal generating function,UGF)的制造系统可靠性分析方法。首先利用随机过程方法建立制造系统各单元的马尔可夫模型,求解各单元状态概率,利用Lz变换,确定各单元的UGF模型,然后通过复合运算得到整个系统的UGF模型。同时利用遗传算法对系统转移密度矩阵进行了优化求解,得到系统的转移密度矩阵,建立系统的马尔可夫可靠性模型,实时有效地对系统各项性能指标进行分析。结合数值案例,验证了所提方法的可行性和有效性,对工程应用具有参考意义。When the traditional reliability analysis method is used to solve complex multi-state system problems,the system cost is often increased,which causes high computational cost and low precision.Aiming at this situation,proposes a manufacturing system reliability analysis method based on Markov stochastic process method and universal generating function(UGF).Firstly,the Markov model of each unit of the manufacturing system is established by using the stochastic process method to solve the unit state probability.The UGF model of each unit is determined by Lz transformation,and then the UGF model of the whole system is obtained through compound operation,at the same time,the transfer density matrix of the system is optimized and solved by genetic algorithm,and the markov reliability model of the system is established.Combined with numerical examples,the feasibility and effectiveness of the proposed method are verified.The new method has reference significance for engineering applications.

关 键 词：马尔可夫 通用生成函数 制造系统 遗传算法 可靠性 

分 类 号：TB332[一般工业技术—材料科学与工程]