论合山电厂330MW机组汽轮机调速系统建模

文章介绍了调速系统模型参数的一些基本概念及建模试验的方法、过程，分析了合山电厂330MW机组汽轮机调速系统建模测试的结果。     

一种算法改进的模糊神经网络及其性能分析

将T-S模糊模型与前馈神经网络相融合构造了一种新型的模糊神经网络,该模型采用基于梯度下降法和算法相结合的混合学习方法,其中梯度下降法用来训练高斯型隶属度函数的非线性参数,而算法用来训练线性参数,即权值。从理论上,证明了该模型对非线性函数的万能逼近能力。仿真实验表明,该模糊神经网络用于非线性动态系统辨识的有效性。     

基于Arena的汽车涂装物流过程仿真研究

对汽车生产线中的涂装物流过程进行了设计与仿真。先设定仿真目标,对仿真案例进行假设,然后利用Arena仿真软件进行具体模型的设计与建立。在建模过程中,对不同方案及相应的参数进行调试,对比了不同建模方案的相同参数以及同种建模方案内不同参数之间的关联性。     

基于飞行器模型的控制器仿真分析

根据飞行器姿态控制方程和流体力学方程,建立动态模型,采用系统仿真的方法及MATLAB软件,通过不同的控制器对飞行模型进行研究,包括PID控制器、自适应模糊控制器的设计。通过外界干扰信号对飞行器控制系统的性能影响进行分析,从超调量、稳态误差、抗负载扰动能力、对参数变化适应能力、鲁棒性等角度研究,得出不同控制器对飞行器不同性能的指标。     

模糊数学在井工开采中的应用

简述了模糊数学的发展简史,着重分析了模糊数学在采矿工程中的应用,包括采动影响下建筑物损害程度的模糊聚类分析、采空区灾害危险度的模糊综合评价、采矿方案的模糊优选、模糊综合评价法在矿山地质灾害分析中的应用、模糊综合评判法在矿井通风系统安全评价中的应用、综采工作面参数系统多维灰色状态模型、岩石强度等级的模糊评价。并且介绍模糊数学的基本方法与步骤,分别列举模糊数学优化理论与模型的建立、模糊聚类分析的一般步骤、综合评价模型及综合评级步骤。     

基于UG的汽车后视镜逆向曲面建模

逆向工程中基于点云数据重建高质量的曲面建模为关键技术,构建模型参数化在产品制造过程中至关重要,非参数化的曲面模型在产品模具设计及数控加工过程中会出现困难。UG在正向产品三维设计中有着广泛的应用,结合UG可参数化建模特点,文章讨论了依据点云数据构建参数化模型的基本原理,给出了利用点云数据构建参数化建模方法。通过汽车后视镜产品点云数据,利用文章给出的基本建模方法,并利用UG进行产品逆向建模,验证了此方法可行有效。     

基于振动传递的车辆悬挂参数选择方法研究

文章应用振动传递理论,对复杂车辆悬挂系统做出合理简化,讨论了使用简化模型进行初步悬挂参数选择的方法,结合多体动力学建模仿真分析,研究了基于实测轨道谱的不同刚度阻尼参数对车辆的一系和二系振动传递倍率的影响规律,进而提出了基于振动传递的车辆悬挂参数选择方法。还研究了分析悬挂参数与振动传递倍率间规律的简单可行方法,能够为轨道车辆动力学分析、转向架悬挂参数设计选型提供指导,具有一定的参考价值。     

基于混杂自动机的装备仿真训练机理建模方法研究

在装备操作仿真训练的机理模型建模过程中,由于训练内容较多、装备工作状态复杂,难以建立表达明确的面向操作训练的机理模型。针对这种情况,基于混杂自动机理论提出适合装备操作系统的自动机模型,并对其建模实现方法进行研究,提出了一种利用Simulink/Stateflow建立离散系统模型,并且按照不同的训练内容和装备工作状态建立多个连续系统模型的机理建模解决方案,在实际应用中,提高了建模及工作效率。     

基于AutoMod的滑块式自动分拣系统的仿真建模实现

在分析滑块式自动分拣系统的机械结构、机械作业过程、工作原理和关键工作参数的基础上,结合分析AutoMod三维建模中设备单元库的可重复使用性特点后,根据滑块式自动分拣系统的机械组成结构来合理划分建模的基本单元模块,并分为静态建模和动态建模两部分。最后采用AutoMod软件建立其仿真模型。详细给出了各模块的建模过程、方法思路及实现某一功能的程序代码思路,实现各模块静态建模和各功能代码的一定程度上的可重复使用性。     

渐开线齿轮参数化设计在UGNX下的完全实现

UGNX中的齿轮参数化建模方法比较繁琐,存在很多重复性工作,从而导致工作效率低下。文章研究了渐开线齿轮全参数化数学模型的建立,提出了在UGNX环境下实现渐开线齿轮的全参数化建模的新方法,通过该方法真正建立了参数化的齿轮模型,为渐开线齿轮系列化建模提供了方便,提高了齿轮设计的销量,降低了齿轮设计周期。     

基于模糊控制的冷库能量优化研究

为了减小冷库目前的能耗,提出采用模糊控制策略的能量优化策略,给出了基于自适应模糊控制的系统控制体系结构,制定了模糊推理规则和隶属度函数,使得制冷设备按照合理优化的方法运行,实验结果表明了所提能量优化策略的有效性和可行性。     

A Mathematical Programming Approach for Measuring Technical Efficiency in a Fuzzy Environment

A three stage approach is proposed to measure technical efficiency in a fuzzy environment. This approach uses the traditional data envelopment analysis framework and then merges concepts developed in fuzzy parametric programming (Carlsson and Korhonen, 1986). In the first stage, vague input and output variables are expressed in terms of their risk-free and impossible bounds and a membership function. This membership function represents the degree to which a production scenario is plausible. In the second stage, conventional efficiency measurement models (Banker, Charnes and Cooper, 1984; Deprins, Simar and Tulkens, 1984) are re-formulated in terms of the risk-free and impossible bounds and the membership function for each of the fuzzy input and output variables. In the third stage, technical efficiency scores are computed for different values of the membership function so as to identify uniquely sensitive decision making units. The approach is illustrated in the context of a preprint and packaging manufacturing line which inserts commercial pamphlets into newspapers.     

Epidemic forecasting with a new fuzzy regression equation

The traditional fuzzy regression model involves two solving processes. First, the extension principle is used to derive the membership function of extrapolated values, and then, attempts are made to include every collected value with a membership degree of at least h in the fuzzy regression interval. However, the membership function of extrapolated values is sometimes highly complex, and it is difficult to determine the h value, i.e., the degree of fit between the input values and the extrapolative fuzzy output values, when the information obtained from the collected data is insufficient. To solve this problem, we proposed a simplified fuzzy regression equation based on Carlsson and Fullér’s possibilistic mean and variance method and used it for modeling the constraints and objective function of a fuzzy regression model without determining the membership function of extrapolative values and the value of h. Finally, we demonstrated the application of our model in forecasting pneumonia mortality. Thus, we verified the effectiveness of the proposed model and confirmed the potential benefits of our approach, in which the forecasting error is very small.     

Intuitionistic fuzzy sets in questionnaire analysis

Fuzzy sets represent an extension of the concept of set, used to mathematically model veiled and indefinite concepts, such as those of youth, poverty, customer satisfaction and so on. Fuzzy theory introduces a membership function, expressing the degree of membership of the elements to a set. Intuitionistic fuzzy sets and hesitant fuzzy sets are two extensions of the theory of fuzzy sets, in which non-membership degrees and hesitations expressed by a set of experts are, respectively, introduced. In this paper, we apply intuitionistic fuzzy sets to questionnaire analysis, with a focus on the construction of membership, non-membership and uncertainty functions. We also suggest the possibility of considering intuitionistic hesitant fuzzy sets as a valuable theoretical framework. We apply these models to the evaluation of a Public Administration and we assess our results through a sensitivity analysis.     

基于突变理论的高校稳定状况动态模糊评价研究

从稳定状态到不稳定的过程是一个复杂并且包含有着大量的突发性非连续性变化过程,为了研究和发现导致学校稳定状况产生突变的因素,科学地评判并预警,本文结合突变理论,运用模糊隶属函数和突变级数,将突变理论与模糊分析结合起来,对与学生有关的学校稳定系统进行多层目标分解,再根据归一公式进行量化递归运算,最后得到学校稳定总突变隶属函数值,进而通过分析不同时期学校稳定总突变隶属函数值及其变化趋势,动态地对学校稳定状况进行模糊综合评判并通过实例进行了检验。     

往复式空气压缩机模糊故障诊断

针对某煤矿空压机站往复式空压机故障诊断的要求,以模糊(Fuzzy)理论为依据,构建了一种往复式空压机模糊故障诊断模型。采用求距离的方法构造隶属度函数,求得待诊断对象对各个典型故障的隶属度,再由最大隶属度原则确定故障原因。该诊断模型可以根据往复式空压机的故障征兆进行有效的故障监测和诊断,可以方便的实现智能诊断。对煤矿上以及其它领域的大型设备状态监测和诊断也有重要参考价值。     

不确定环境下核电项目进度动态优化控制分析

针对核电项目进度控制的不确定性特点,应用隶属度函数法构建了核电进度计划的模糊目标及模糊约束的模糊集成模型,然后应用并行遗传算法分析了进度计划动态优化调整问题,并以某核电项目进度计划为例,对工期、成本进行了不同可能性水平下的协调优化,为进度控制提供了决策依据。     

Fuzzy modelling of static system optimum traffic assignment problem having multi origin-destination pair

Traffic congestion is an unpreventable problem to avoid in a transportation network and it has negative effects on traffic accident, time wasting, traffic delay and safety problem. Besides, in transportation networks, drivers do not want to deal with traffic jam while traversing between specified origin-destination pair. Therefore, traffic assignment (TA) is imperative to improve traffic management, transportation safety, time, and cost savings. System Optimum Traffic Assignment Problem (SOTAP) is a kind of TA model which aims to minimize the total system travel time on the network, and satisfies the flow conservation constraints. To model the SOTAP more realistically, the imprecise parameters can be taken as fuzzy. Therefore, in this paper, we focus on converting the conventional SOTAP to a fuzzy quadratic programming problem (QPP) which is named System Optimum Fuzzy Traffic Assignment Problem (SOFTAP). Here, link travel time is expressed with BPR function as generally used in the literature by converting to fuzzy except link-dependent parameters. Thus, the nonlinear objective function of SOFTAP is expressed in terms of fuzzy link flows and fuzzy link travel times. A solution approach from the literature is modified to the reconstructed SOFTAP.     

基于模糊优选模型的节能减排政策综合效果评价及其应用研究

通过建立节能减排政策效果评价指标体系,将模糊优选模型与群组层次分析法有效地结合,并将这一方法应用到具体的行业分析中。结果表明,模糊优选模型能较好应用于实际。它不但能有效减少数据信息损失,而且在一定程度上避免了隶属度函数的“主观任意性”,非常适合应用于政策效果评价研究领域。     

考虑需求不确定的订单分配模型研究

从顾客需求不确定性出发,在考虑批量折扣的情况下,构建了一个基于成本、延迟交货数量、质量和交货提前期的具有模糊权重的多目标订单分配模型。在求解过程中,用隶属度函数表示决策者对各目标值的满意程度,用梯形模糊数来表示各指标的权重,然后将多目标规划问题转化为求全局满意度最优的单目标规划问题。最后通过一个数值算例说明了模型的求解过程。