基于改进遗传算法的系统可靠性分配优化

为了实现系统可靠性分配的优化,以研制成本为目标函数,通过修正广义成本函数,建立系统可靠性分配优化模型。结合可靠性单元的复杂度、技术成熟度、工作时间、使用环境实现广义成本的定量评估。根据模型特点,改进基本遗传算法进行问题的求解。通过多种群进化策略减少未成熟收敛的发生,构造带有惩罚项的适应度函数实现多个约束条件的融合,并选择适当的遗传算子提高遗传算法效率。通过算例证明新算法在模型求解方面具有更高的搜索效率。     

基于费用函数的系统可靠性优化分配方法

研究了系统可靠性优化分配问题.首先以费用最小为目标函数构建了非线性规划模型,然后建立了一种新的费用函数模型,分析了各参数对费用函数的影响,最后采用Lagrange乘子法求解,得到各单元的可靠性优化分配值.算例表明这种费用函数模型参数含义清楚,便于确定,利于工程应用.     

串联机械系统可靠性优化设计的准则法

对于串联机械系统可靠性优化设计模型,往往由于其维数较高,用常规方法对整体模型较难进行求解。本文根据模型的最优准则,构造了一种迭代求妥方法。在迭代过程中只需求解维数较低的单元部件可靠性优化条件模型,因此,既便于使用常求解,又便于使用机械零部件可靠性优化设计的现有成果。最后给出了简单算例。     

机械系统整体可靠性优化设计的分解协调法

根据大系统理论的分解协调原理，提出了机械系统整体可靠性优化设计的分解协调法。该方法将机械系统整体可靠性优化设计模型的求解，转化为对其各组成零部件可靠性优化设计模型的迭代求解，从而既可解决由于机械系统整体可靠性优化设计模型的庞大而带来的“维数灾难”问题，又可充分利用机械零部件可靠性优化设计的现有成果。最后给出了简单算例以证明算法的有效性。     

考虑多模相关的机械系统可靠度优化模型

相关性是复杂机械系统的固有特性,也是影响和制约机械可靠性研究工作的重大难题。以往的可靠性研究多数以独立性假设为前提,文中从结构系统二阶窄界限理论出发,研究和分析在考虑多模式失效相关时的机械系统可靠性,详细探讨如何进行可靠度上下界限值的优化,并将优化后的模型用于分析实际机械系统的可靠度,结果证明优化后的二阶界限模型在机械系统可靠性分析、预测和研究中有很强的针对性和有效性。     

串联机械系统可靠性优化设计的目标协调法

根据大系统理论的分解协调原理，提出了串联机械系统可靠性优化设计的目标协调法。该方法将串联机械系统可靠性优化设计整体模型的求解，转化为对各组成单元体可靠性优化设计模型的迭代求解，从而降低了优化模型的维数，给解决问题带来了方便。最后给出了简单算例以证明算法的有效性。     

复杂系统可靠性冗余优化的量子粒子群算法研究

由于复杂系统可靠性函数常常具有非线性的特点,因此如何确定复杂系统各单元冗余数,设计既满足可靠度要求、又使系统成本最小是冗余优化问题中的难点.针对复杂系统的特点,提出了基于量子粒子群算法的求解方法.根据数学模型,详细探讨了量子粒子群算法在系统的可靠性优化计算中应用的可行性,并给出了基于粒子群算法的可靠性的求解策略,同时对桥式系统的可靠性优化设计问题进行分析计算.仿真表明,该算法具有较强的局部搜索能力,与其他方法相比,该算法有较高的搜索效率,能够找到更优的解.最后验证了该算法在复杂系统可靠性优化中的可行性和有效性.     

可靠性优化问题的人工鱼群算法求解

为了使设计既能满足可靠度要求又使系统成本最小,提出了基于人工鱼群算法的优化方法。简单介绍了冗余优化模型和人工鱼群算法,并给出了基于人工鱼群算法的可靠性的求解策略,详细讨论了求解步骤,并对串一并联系统的可靠性分配的可靠性优化设计问题进行了分析计算。结果表明该算法具有较强的局部搜索能力,与其他方法相比,具有更高的搜索速度和搜索效率。     

可靠性优化问题的人工鱼群算法求解

为了使设计既能满足可靠度要求又使系统成本最小,提出了基于人工鱼群算法的优化方法.简单介绍了冗余优化模型和人工鱼群算法,并给出了基于人工鱼群算法的可靠性的求解策略,详细讨论了求解步骤,并对串-并联系统的可靠性分配的可靠性优化设计问题进行了分析计算.结果表明该算法具有较强的局部搜索能力,与其他方法相比,具有更高的搜索速度和搜索效率.     

圆柱螺旋压缩弹簧的多学科协同优化设计

引入多学科设计优化理论解决圆柱螺旋压缩弹簧的优化设计问题。针对圆柱螺旋弹簧优化设计存在的多目标、多约束特点,建立了圆柱螺旋压缩弹簧的多学科优化设计模型,并采用协同优化算法,完成了优化模型的求解。优化结果证明了协同优化算法解决圆柱螺旋压缩弹簧的优化设计优化问题的有效性,为解决更为复杂机械系统的设计优化问题奠定了基础。     

基于耦合分析与加权满意度的机械系统多目标协同优化方法

针对机械系统优化中因设计变量耦合关联导致的优化结果可靠性问题,提出了基于加权满意度的耦合关联机械系统多目标协同优化方法。建立机械系统设计变量耦合关联模型,采用最大-最小满意度函数法,并考虑各子目标的相对权重,建立基于权重加权和的多目标协同优化评价函数,将多目标优化问题转变为单目标优化问题。以掩护式液压支架四连杆机构-结构多目标协同优化为对象的应用表明,提出的方法简化了耦合关联机械系统多目标优化求解的复杂度,而且提高了优化结果的可靠性。     

Decomposition method of complex optimization model based on global sensitivity analysis

The current research of the decomposition methods of complex optimization model is mostly based on the principle of disciplines, problems or components. However, numerous coupling variables will appear among the sub-models decomposed, thereby make the efficiency of decomposed optimization low and the effect poor. Though some collaborative optimization methods are proposed to process the coupling variables, there lacks the original strategy planning to reduce the coupling degree among the decomposed sub-models when we start decomposing a complex optimization model. Therefore, this paper proposes a decomposition method based on the global sensitivity information. In this method, the complex optimization model is decomposed based on the principle of minimizing the sensitivity sum between the design functions and design variables among different sub-models. The design functions and design variables, which are sensitive to each other, will be assigned to the same sub-models as much as possible to reduce the impacts to other sub-models caused by the changing of coupling variables in one sub-model. Two different collaborative optimization models of a gear reducer are built up separately in the multidisciplinary design optimization software iSIGHT, the optimized results turned out that the decomposition method proposed in this paper has less analysis times and increases the computational efficiency by 29.6%. This new decomposition method is also successfully applied in the complex optimization problem of hydraulic excavator working devices, which shows the proposed research can reduce the mutual coupling degree between sub-models. This research proposes a decomposition method based on the global sensitivity information, which makes the linkages least among sub-models after decomposition, and provides reference for decomposing complex optimization models and has practical engineering significance.     

以可靠度为目标的机械大系统优化设计的分解法

提出了一个三级分解算法 ,用来求解以可靠度为目标的三级机械大系统优化设计的数学规划模型。首先利用 Kuhn- Tucker条件将高维数的系统整体优化模型分解为三级低维数的优化模型 ,然后给出了联立求解三级优化模型的迭代法。     

An emotional learning-based fuzzy inference system for improvement of system reliability evaluation in redundancy allocation problem

A major challenge in reliability based optimal design problems is the evaluation of system reliability given a system design. Reliability evaluator is a tool, a model, or a system that analyses the reliability of a system given a specified system design. Reliability evaluator usually is embedded in reliability optimization model and it can be seen as a computational engine that can provide optimization model with the value of its objective function. Enhancing performance of the reliability evaluator in optimization models is important as the overall performance of optimization model is significantly affected by its embedded reliability evaluator. The purpose of this paper is to present an approach to improve the accuracy and generalization ability of evaluating system reliability in redundancy allocation problem. The main idea is to employ emotional learning-based fuzzy inference system (ELFIS) to improve performance of reliability evaluator. A series–parallel case reliability–redundancy allocation is considered and the proposed ELFIS is validated by comparison of its results with those of multi-layer perceptron neural network and adaptive network-based fuzzy inference system. Normalized mean squared error and mean absolute percentage error show that ELFIS can bring better accuracy in evaluating the system reliability for those reliability-based optimal designs.     

基于灵敏度分析的稳健可靠性优化设计模型及MATLAB实现

在机械零件的可靠性优化设计中,普遍存在约束的作用,且最优解往往位子可行域的边界上。由于外界环境的变化或人为因素造成设计变量扰动,可能使设计成为不可行。本文提出了一种基于设计变量敏感度的稳键性设计方法,建立了基于灵敏度分析产生附加目标函数的两种稳健可靠性优化设计模型,并用 ＭＡＴＬＡＢ语言的优化工具箱和符号工具箱来实现机械零件的稳健可靠性优化设计,计算实例说明所述模型的可行性与实用性。     

基于可靠性仿真面向维护的刮板输送机链条优化设计

基于刮板圆环链的失效时间分布函数,重构了面向维护的刮板链可靠性模型,对刮板链服役运行过程中的可靠性变化进行仿真分析;建立了综合考虑系统维护周期、全寿命周期成本和系统可靠度的刮板链优化设计模型,提出了基于可靠性仿真的刮板链优化设计方法。仿真结果表明,该设计方法可以优选系统的刮板链设计方案,合理选择圆环链的配置,优化系统的维护周期。     

一类多层生产排序问题的建模与求解

针对一类航天企业普遍存在的多层生产排序问题,建立了整体优化模型,并根据多层生产排序的特点,提出了一种分解-协调的建模思想及其求解策略.在建立三层子问题独立优化模型的基础上,依据各层工件可开工时间及设备最早可用时间对优化解进行自下而上的协调,逐步获得各层子问题的最优解,进而获得整体问题的满意解.采用该方法对来源于实际企业的多层排序问题进行建模和求解,所得结果较实际结果有显著提高,验证了其有效性和实用性.     

基于MDO方法的离心式压气机设计系统

针对离心式压气机设计中存在流-热-固耦合的问题,文中进行离心式压气机的多学科设计优化研究,基于多学科可行方法,建立离心式压气机的多学科设计优化系统.利用非均匀有理B样条曲线和五次多项式,分别构建径流式叶片型线和扩压器叶片型线,通过特征造型技术,建立离心式压气机参数化模型.采用线性插值方法和网格重生成方法,完成对温度、气压和变形耦合信息传递.在压气机参数化建模和多学科耦合分析的基础上,以总压比、等熵效率和流量为优化目标,对某离心式压气机进行设计优化,实现其综合性能的改善.所建多学科设计优化系统可以推广到其他多场耦合系统的设计.     

Robust tools for prediction of variability and optimization in structural dynamics

The aims of this work were to quantify the effects of uncertainties of design parameters on the variability of linear and non-linear behaviour of mechanical structures that we wish to optimize, and to calculate optimal and robust solutions resulting from numerical simulations. We propose a method that takes into account the propagation of uncertainties in finite-element models in a multi-objective optimization procedure. This method is based on coupling the stochastic response surface method (SRSM) and the non-dominated sorting genetic algorithm (NSGA). SRSM is based on application of the stochastic finite-element method via the polynomial chaos expansion method or the modal perturbation method. This strategy avoids the use of Monte Carlo simulation, in which costs can become prohibitive in optimization problems, especially when the finite-element models are large and have a considerable number of design parameters. The robust design described here has been developed to obtain an optimum value that is insensitive to changes of design variables within a feasible range.     

Air-bearing position optimization based on dynamic characteristics of ultra-precision linear stages

Air-bearings are installed between the stator and the mover of ultra-precision linear stages to suppress vibration and mechanical contact. Spring-damping elements are used to emulate the complex interaction of the finite element model (FEM) developed in this paper and the system dynamic behaviors are analyzed. Through the experimental modal test, the validity and reliability of the model are proven. However, the dynamic characteristics including mode frequency, mode shape, and response amplitude are obviously changed with the position of air-bearings. The combined optimization method is used to optimize the air-bearings position. The best and worst positions are obtained using the dynamic characteristic analysis. The method can be generalized to the connection position of different components in manufacture elements and to implement the system dynamic characteristics optimization when the connection position can be changed.