摆线针轮行星减速器的稳健可靠性优化设计

提出一种可以提高产品可靠性的稳健可靠性优化设计方法.在一般可靠性优化设计的基础之上考虑稳健性的要求,通过可靠度对不确定性参数的敏感度最小达到设计质量稳健性的要求.以此方法建立摆线针轮行星减速器稳健可靠性优化设计模型,并以实例进行优化计算.     

汽车鼓式制动器的可靠性稳健优化设计

在汽车鼓式制动器设计中考虑不确定因素的影响,将可靠性优化理论、可靠性灵敏度分析与稳健设计方法相结合,以制动效能因数为目标函数建立制动器可靠性稳健优化数学模型。把制动力矩、摩擦衬片压力的可靠性灵敏度溶入可靠性优化设计模型之中,将可靠性稳健优化设计转化为满足可靠性要求的多目标优化问题。实例计算表明,稳健优化后的制动器不仅有较高的制动效能和可靠性,还具有较低的可靠性灵敏度,取得了满意的结果。     

二齿差滚动活齿传动多目标稳健优化设计

为了提高二齿差滚动活齿传动的设计水平和设计质量,将优化设计理论与稳健设计方法相结合,在考虑设计变量和设计常量的偏差对可行域影响的基础上,建立了二齿差滚动活齿传动的多目标稳健优化设计数学模型.基于模拟退火算法,提出了该模型的求解方法,给出了计算实例.计算结果表明:与应用普通优化方法得出的优化结果相比较,基于模拟退火算法的稳健优化设计所得的二齿差滚动活齿传动的体积缩小24.1％.     

双卷螺旋弹簧模糊可靠性优化设计

在传统设计方法的基础上,利用模糊可靠性理论和优化设计方法,建立了双卷螺旋弹簧模糊可靠性优化设计模型.通过转8A转向架摇枕弹簧的优化设计结果与原设计结果的对比分析表明本文所建立双卷螺旋弹簧模糊可靠性优化设计模型具有一定的合理性和实用性.     

自卸车货箱多学科优化设计

对某自卸车货箱进行包括线性静力和振动模态的多学科优化,并对优化结果进行了稳健性设计,确定了在随机误差影响下多学科优化结果的可靠性。首先建立了自卸车货箱的有限元模型,通过灵敏度分析筛选设计变量;其次应用试验研究方法采集试验样本并拟合各个响应的响应面,基于响应面优化计算获得多学科优化的最优解;最后通过稳健性分析确定了优化结果的可靠性。经过多学科优化设计,自卸车货箱在刚度、强度、第一阶模态频率不降低的情况下,质量减少8%。     

基于模糊理论的车辆变刚度弹簧组可靠性优化设计

为提高变刚度弹簧组的设计质量,在传统优化设计方法的基础上,应用模糊设计理论和可靠性设计理论,建立了当弹簧应力和强度分别为随机变量和模糊变量时,综合考虑静强度、疲劳强度、稳定性、质量等因素的变刚度弹簧组的模糊可靠性优化设计模型.以货车某新型变刚度弹簧组为研究对象,利用建立的模型对其进行了优化设计分析,计算结果显示,空重车静挠度分别比原设计方案提高了5.4和3.2 mm,同时还使其总质量降低了约15.8%,表明所建立的模糊可靠性优化设计模型能满足设计要求.      

高速动车组齿轮箱稳健优化设计

将高速动车组齿轮箱体积作为目标函数,利用灵敏度分析法分析约束函数对不确定因素的波动情况,选出最大波动函数为附加目标函数,使高速动车组齿轮箱体积及实现约束函数对不确定因素的最大波动同时达到最小,进而缩小齿轮箱体积的波动范围,利用物理规划法将双目标函数转化为单目标函数进行优化计算.算例表明,稳健优化设计方法能使齿轮箱体积达到稳健优化目的,并为动车组其它零部件的稳健优化设计提供参考.     

稳健性优化方法在铁道车辆优化中的应用

采用一种基于灵敏度分析的稳健性优化方法,以某铁道车辆转向架悬挂参数为设计变量,针对该车辆的稳定性进行了优化设计,并结合正交试验参数灵敏度分析方法对优化后的悬挂参数进行了灵敏度分析.研究结果表明,稳健性优化设计得到的悬挂参数不仅使该车辆拥有较高的临界速度,且临界速度对各悬挂参数的灵敏度均很低,文中优化后车辆的临界速度达到了505 km/h,当各悬挂参数改变时,临界速度变化不到5％.     

企业物流中心稳健性选址模型

借鉴稳健设计的基本思想,运用随机机会约束规划方法,建立了需求和制造中心加工量不确定条件下的企业分销物流中心的稳健性选址模型,该模型通过将不确定条件下选址分派费用的波动均方差融入目标函数以实现选址稳健性目标。分析了该类模型的处理方法,探讨了基于组合遗传算法的模型求解思路,并通过算例进行了验证。分析结果表明:与普通模型相比,该模型在整个规划期内选址分派费用的波动均方差降低31.5%,物流网络稳健性显著提高,该模型合理有效。     

摆线针轮行星传动的可靠性优化设计

将可靠性设计方法引入优化设计中 ,用于摆线针轮行星传动的设计 ,建立了以体积最小为目标的可靠性优化设计概率数学模型 ,且根据实例进行了分析计算     

Structural Multi-objective Probabilistic Design for Six Sigma

Uncertainties in engineering design may lead to low reliable solutions that also exhibit high sensitivity to uncontrollable variations. In addition, there often exist several conflicting objectives and constraints in various design environments. In order to obtain solutions that are not only "multi-objectively" optimal, but also reliable and robust, a probabilistic optimization method was presented by integrating six sigma philosophy and multi-objective genetic algorithm. With this method, multi-objective genetic algorithm was adopted to obtain the global Pareto solutions, and six sigma method was used to improve the reliability and robustness of those optimal solutions. Two engineering design problems were provided as examples to illustrate the proposed method.     

A novel approach to design robust fault detection filter for networked control systems

In this paper, an approach for designing robust fault detection filter (RFDF) of networked control systems (NCSs) with unknown inputs is studied. The design aims at implementing the optimal trade-off between robustness of unknown inputs (including the item produced by networked-induced delay) and sensitivity of fault. The key design issue is to introduce an optimal fault detection filter based on NCSs with the control law compensation as the reference residual model of NCSs and to formulate the RFDF design as a model-matching problem. By applying H _∞ optimization technique, linear matrix inequality (LMI) approach is given to solve the model-matching problem. The validity of the proposed approach is shown by a numerical example.      

Robust Optimization Design of Metro Handrails

This paper presents the robust design and response surface method(RSM) based on finite element analysis for the optimization design of metro handrails. The response surface can be created for each output parameter. Sequential quadratic programming is used for the optimization of metro handrails. Taguchi design is employed to investigate the sensitive controlling factors for the strength and mass of metro handrails, by taking the material density, the column and cross bar thickness as controlling factors, and the acceleration, the elastic modulus and the fluctuation of material density as uncontrollable factors. Then, the best combination of controlling factors is found. The results by different methods show that the method of Taguchi design can improve the robustness of the structural performance and reduce the mass.     

Robust expected violation criterion for constrained robust design problems and its application in automotive lightweight design

Metamodeling techniques are commonly used to replace expensive computer simulations in robust design problems. Due to the discrepancy between the simulation model and metamodel, a robust solution in the infeasible region can be found according to the prediction error in constraint responses. In deterministic optimizations, balancing the predicted constraint and metamodeling uncertainty, expected violation (EV) criterion can be used to explore the design space and add samples to adaptively improve the fitting accuracy of the constraint boundary. However in robust design problems, the predicted error of a robust design constraint cannot be represented by the metamodel prediction uncertainty directly. The conventional EV-based sequential sampling method cannot be used in robust design problems. In this paper, by investigating the effect of metamodeling uncertainty on the robust design responses, an extended robust expected violation (REV) function is proposed to improve the prediction accuracy of the robust design constraints. To validate the benefits of the proposed method, a crashworthiness-based lightweight design example, i.e. a highly nonlinear constrained robust design problem, is given. Results show that the proposed method can mitigate the prediction error in robust constraints and ensure the feasibility of the robust solution.     

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本文提出了关于交通运输与土地利用的综合模型的连续最优化及敏感性分析的基本框架。考虑外生交通费用的土地利用模型的敏感性分析和考虑弹性需求的交通运输网络的敏感性分析过程本是相互独立的，本文将两者结合为一个综合模型的敏感性分析。将这种敏感性分析方法用于土地利用方案设计和交通运输政策制定的最优化，可以使一定的社会剩余函数最大化。最后，本文以一个包含拥挤交通网络子模型的住宅分布模型为例对所提出方法进行进一步说明。     

ROBUST SMITH PREDICTIVE CONTROLLER FOR PROCESS WITH INVERSE RESPONSE

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Continuous Optimization Method for Integrated Land Use/Transportation Models

A basic framework for the sensitivity analysis and continuous optimization of integrated land use/transportation model is proposed in this paper. It is shown that separate sensitivity analysis procedures for a land use model with exogenous travel costs and a transportation network with elastic demand can be combined to get a sensitivity analysis procedure for the integrated model. Sensitivity-analysis-based techniques can then be used for the optimal design of land use plans and transportation policies so that certain social surplus functions are optimized. The proposed method is illustrated with a residential location model with a congestible transportation network sub-model.     

基于形式化方法的道口控制系统规范建模与验证

为了增强铁路道口控制系统设计的可靠性,使用一种形式化方法对该系统进行建模与验证. 基于道口管理规范,在分析系统各类属性与事件流程的基础上,使用UML图方法并结合精化策略建立了系统各层的Event-B语言模型. 通过对不变式的证明义务进行证明,验证了系统设计中的安全、时间特性,检查出了需求规范分析中的缺陷,提出了增强系统稳健性的改进方案,修正了系统的设计原型. 最后,通过不变式冲突与死锁检验进一步确认了模型的正确性. 研究表明文中方法提高了形式化建模过程的准确性与层次性,且确认得出目前规范中存在列车驶入道口时不能确保道口出清的缺陷,证实了使用本文形式化流程可以验证道口控制系统的需求规范并形成可靠的设计原型,从而可提高铁路道口的安全性.      

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复杂交通场景由于背景构造困难限制了视频监控技术的应用. 为了解决这个问题,本文提出了一种新的基于传感器融合的复杂交通视频背景构造方法. 首先通过基于EM算法的高斯混合模型提高背景建模的准确性;其次,对于运动缓慢或者静止的区域,通过设定不同的采样频率来提高背景建模数据的可靠性;对来自线圈和虚拟检测线检测到的数据进行数据融合来提高虚拟线圈检测车速的精度,通过引入局部稳态最优Kalman平滑器提高了数据融合算法的自校正能力. 最后,实验结果证明了所提方法的有效性.