基于计算机模拟平台的蒸馏过程仿真研究

以过程模型为基础在C++BUILDER环境下设计并实现的蒸馏过程计算机模拟平台,为研究蒸馏过程提供了过程模拟的计算机环境。模拟平台具有在线过程模拟功能和开放的接口环境,适于各种模拟方案、过程模型和算法的仿真研究。基于该平台,可以方便地对蒸馏过程进行稳态模型、动态模型、优化模型和控制模型的仿真计算,检验模型和算法的有效性,并可针对过程特点进行分析并提供优化操作指导值。     

Visualisation in the Simulation and Control of Economic Models

Simulation of economic models is frequently used in the investigation of economic policy. Yet one of the problems with simulation is that it can be difficult to appreciate the model properties due to the nature of the simulation process. Stochastic simulation, for example, can produce large quantities of output which can be difficult to comprehend. Further, when mathematically sophisticated techniques such as the use of optimal control and Kalman Filtering are applied to models, the simulation process can become even more complex. Visualisation techniques in model building, simulation, and analysis of simulation output can help reduce the complexity. This is especially the case with interactive simulation. In this paper we investigate the use of visualisation in simulation by examining the application of optimal control techniques to a stochastic forward looking analytic economic model. We also use interactive object oriented simulation software where objects, such as components of models or graphs of outputs, can be visually manipulated to form simulation systems. We find that the use of visualisation can make the investigation of policy analysis issues with such models more comprehensible.     

Model-predictive control of feed flow reversal in a reverse osmosis desalination process

Model-predictive control algorithms are applied to a high capacity reverse osmosis (RO) membrane desalination process simulation that utilizes feed flow reversal in order to prevent and/or reverse scale crystal formation on the membrane surface. A dynamic non-linear model which incorporates feed concentration and membrane properties is used for simulation and demonstration of optimally controlled feed flow reversal. Before flow reversal can take place on a high capacity RO plant, the flow into the membrane unit must be carefully reduced to eliminate the risk of membrane module damage and unnecessary energy consumption. A cost function is formulated for the transition between the normal high flow steady-state operating point to a low flow steady-state operating point where it is safe to reverse the flow direction. Open-loop and closed-loop simulations demonstrate non-linear model-predictive control strategies that induce transition from the high-flow to low-flow steady-states in an optimal way while subjected to plant-model mismatch on the feed concentration, actuator magnitude and rate constraints, and sampled measurements.     

过热气温的多内模自适应内模控制的研究

针对电厂过热汽温被控对象具有大惯性、大滞后特性且对象参数随负荷变化较大等因素,提出了一种基于多模型的自适应内模控制策略。通过在不同工况辨识得到其多模型,设计出相应的内模控制器,根据运行工况选择相应的控制器,从而实现全工况运行的自适应;同时以火电厂过热汽温被控对象为参考模型设计自适应控制律,使控制器内部模型的参数逐步逼近被控对象的参数直至相等。仿真结果表明,该控制策略比常规的内模控制具有更好的控制品质。     

虚拟未建模动态补偿驱动的双率自适应控制

工业换热过程是蒸汽与循环水在换热器中进行热交换,使供水温度达到工艺规定的目标范围内的复杂工业过程.由于存在蒸汽压力、回水流量波动以及换热器内管壁结垢的扰动,导致被控对象模型参数发生未知随机的大范围变化,使控制器积分作用失效,造成内环蒸汽流量和外环供水温度波动,相互影响,甚至谐振.针对上述问题,利用工业换热过程运行在工作点附近的特点,用确定性低阶线性模型和虚拟未建模动态来描述被控过程.将自适应信号法与双率控制技术相结合,提出了以蒸汽流量为内环输出、以供水温度为外环输出的双率自适应控制器,并给出了该控制器的稳定性和收敛性分析.本文将工业换热过程机理模型作为被控对象,进行了半实物仿真.结果表明,对于工业换热过程,在模型参数大范围变化时,本文提出的控制方法可以将供水温度控制在工艺要求的目标范围内.     

Comparative study of ROC regression techniques—Applications for the computer-aided diagnostic system in breast cancer detection

The receiver operating characteristic (ROC) curve is the most widely used measure for statistically evaluating the discriminatory capacity of continuous biomarkers. It is well known that, in certain circumstances, the markers’ discriminatory capacity can be affected by factors, and several ROC regression methodologies have been proposed to incorporate covariates in the ROC framework. An in-depth simulation study of different ROC regression models and their application in the emerging field of automatic detection of tumour masses is presented. In the simulation study different scenarios were considered and the models were compared to each other on the basis of the mean squared error criterion. The application of the reviewed ROC regression techniques in evaluating computer-aided diagnostic (CAD) schemes can become a major factor in the development of such systems in Radiology.     

基于Fisher 判别分析的过程运行状态在线评价

为了实时掌握生产过程运行状态, 提出一种基于Fisher 判别分析(FDA) 的过程运行状态在线评价方法. 提出 离线数据分类与识别算法, 以识别不同稳定运行状态的建模数据及其对应的状态等级; 利用FDA提取各个稳定运行 状态的特征属性, 建立评价模型; 在线评价时, 通过“时间窗口”数据特征与各个状态等级的相似度, 实时评价过程运行状态. 将所提出的方法应用于某湿法冶金过程的仿真结果验证了该方法的有效性.

     

Multi-model ensemble prediction model for carbon efficiency with application to iron ore sintering process

Iron ore sintering is one of the most energy-consuming process in steel industry. Accurate prediction of carbon efficiency for this process is beneficial to energy savings and consumption reduction. Considering the sintering process exhibits strong nonlinearities, multiple parameters, multiple operating conditions, etc., a multi-model ensemble prediction model based on the actual run data is developed to achieve the high-precision prediction of carbon efficiency. It takes the comprehensive coke ratio (CCR) as a metric (index) of carbon efficiency in the sintering process. First, an affinity propagation clustering algorithm is used to realize the automatic identification of multiple operating conditions. Then, different models are established under different operating conditions by using the proposed least squares support vector machine (LS-SVM) with hybrid kernel modeling method. Finally, a partial least-squares regression method is employed as an ensemble strategy to combine the different models to form the multi-model ensemble prediction model for the CCR. The simulation results involving the actual run data demonstrate that the proposed model can predict the CCR accurately when compared with other prediction methods. The results of actual runs show that the coefficient of determination for the proposed model is 0.877. The proposed model satisfies the requirements of actual sintering process and enables the real-time prediction.     

延迟焦化主分馏塔工艺模拟与分析

本文运用流程模拟软件SimSci／PROⅡ探讨延迟焦化分馏单元的模拟策略。根据延迟焦化分馏单元无法确定反应油气进料组成和塔底存在非平衡级的特点,采用塔出料反推进料油气组成和塔底换热段与精馏段分段处理的办法,选择Grayson- Streed物性选择集进行模拟。模拟结果与现场标定数据基本一致。根据模拟计算结果,对分馏塔操作中存在的问题进行了分析,同时进行了主分馏塔的水力学核算,找出了装置运行存在的瓶颈,提出了相应的解决方案。模拟结果能为装置扩能改造提供依据．并为同类装置的扩能或节能改造提供参考。     

RH真空脱气过程的模拟研究

本文对RH真空脱气过程进行了解析,建立了适合于RH真空脱气过程的物理模型及数学模型。模型能较好地反映 RH 真空脱气过程各主要元素及气相成分的变化规律。传质容量系数作为模型中的唯一可调参数,可表征 RH 真空脱气过程的传递特性及其操作特性。     

基于状态机的自动变速控制器仿真研究

针对汽车发动机自动变速装置在不同运行状态下仿真建模的研究,提出基于有限状态机的建模方法.该方法通过将汽车行驶阶段的不同状态,建模为多状态事件的迁移,借助发动机厂家提供的变速器换挡点图以及发动机工作特性图,利用Matlab/Simulink建立了整车动力性能仿真模型和基于Matlab/     

Recurrent neuro-fuzzy networks for nonlinear process modeling

A type of recurrent neuro-fuzzy network is proposed in this paper to build long-term prediction models for nonlinear processes. The process operation is partitioned into several fuzzy operating regions. Within each region, a local linear model is used to model the process. The global model output is obtained through the centre of gravity defuzzification which is essentially the interpolation of local model outputs. This modeling strategy utilizes both process knowledge and process input/output data. Process knowledge is used to initially divide the process operation into several fuzzy operating regions and to set up the initial fuzzification layer weights. Process I/O data are used to train the network. Network weights are such trained so that the long-term prediction errors are minimized. Through training, membership functions of fuzzy operating regions are refined and local models are learnt. Based on the recurrent neuro-fuzzy network model, a novel type of nonlinear model-based long range predictive controller can be developed and it consists of several local linear model-based predictive controllers. Local controllers are constructed based on the corresponding local linear models and their outputs are combined to form a global control action by using their membership functions. This control strategy has the advantage that control actions can be calculated analytically avoiding the time consuming nonlinear programming procedures required in conventional nonlinear model-based predictive control. The techniques have been successfully applied to the modeling and control of a neutralization process.     

基于多模型的非线性系统自适应最小方差控制

对于一类典型的离散时间非线性系统, 提出了一种基于多模型的自适应最小方差控制方法. 通过在平衡点附近建立线性模型, 用径向基函数神经元网络来补偿建模误差和未建模动态, 形成了非线性系统的多模型表示. 采用了具有积分性质的切换指标函数作为切换法则和最小方差的控制方法构成了多模型自适应控制器. 仿真实验的结果表明了这种方法的有效性.     

一种空战任务可视化仿真系统的开发

为了研究飞机作战武器的作战使用和协同对抗过程,针对新型战斗机作战使用研究需要,提出了一个以某型飞机建立的飞行和武器控制模型,同时研制了模拟座舱,数个座舱之间可以通过网络通信实现多机的协同或对抗系统。利用在FlightGear和Simulink上建立的空战视景仿真系统实现协同对抗可视化任务计算和进行仿真。结果显示,改进方案切实可行,可扩展性强,并为空战武器系统战场环境可视化提供了依据。     

用Flash MX 2004开发离心泵实验仿真课件

使用Flash MX 2004开发了离心泵性能实验仿真课件,课件采用了面向对象技术的编程方式。本文介绍用Flash制作课件的设计思想和主要制作过程,对制作中的一些关键技术有较为详细的阐述。数学模型拟和程度高,课件较好地再现了实际情况,几乎现实中可操作的变量都可以进行仿真操作,能自动记录数据和处理数据。课件具有很好的交互性和可操作性,界面友好,画面美观。     

Estimation of rail capacity using regression and neural network

Railroads have been experiencing traffic demand growth and increasing capacity constraints. Effective capacity management is thus crucial to the successful operation of railroads. The initial step in capacity management is to measure and monitor capacity and congestion. This research established a process for constructing parametric capacity models for single- and double-track railroads with simulation results using both regression and neural network (NN) techniques. Experimental results show that the NN models outperform the regression models in terms of predicting both single- and double-track capacity. Aside from traffic volume, average train speed and siding/crossover spacing were identified as the most sensitive factors relative to rail capacity. The use of this capacity evaluation tool can determine efficiency of current operations and can provide an objective basis to assess the need for capital expansion projects.     

化工过程控制仿真培训系统的开发范式

化工过程控制仿真培训软件系统的开发具有重要的工程应用意义。文章分析了仿真培训系统的功能需求,提出了客户／服务器模式的系统体系结构,采用面向对象的建模方法设计了系统的对象模型。建立的系统体系结构和对象模型具有充分的合理性和通用性,可以作为一般化工过程控制仿真培训系统开发的范式。     

Modelling and control of chaotic processes through their bifurcation diagrams generated with the help of recurrent neural network models. Part 2: An industrial study

Many real-world processes tend to be chaotic and are not amenable to satisfactory analytical models. It has been shown here that for such chaotic processes represented through short chaotic noisy observed data, a multi-input and multi-output recurrent neural network can be built which is capable of capturing the process trends and predicting the behaviour for any given starting condition. It is further shown that this capability can be achieved by the recurrent neural network model when it is trained to very low value of mean squared error. Such a model can then be used for constructing the bifurcation diagram of the process leading to determination of desirable operating conditions. Further, this multi-input and multi-output model makes the process accessible for control using open-loop/closed-loop approaches or bifurcation control, etc.     

面向显示界面工效研究的飞机座舱仿真系统

显示界面工效研究通常以时间和正确率为指标记录分析被试的操纵过程,显示界面需要一定的柔性,现有飞行模拟器无法满足上述需求. 将飞行员操纵飞机的过程分解为信息输入、信息处理、信息输出,记录信息输入、输出变化的时刻及事件,供后续分析研究. 为实现上述要求,明确仿真系统的功能需求、功能模块得出系统总体框架. 详细阐述系统仿真模块、虚拟仪表模块、视景模块、通信模块、数据管理模块的设计过程. 实现并测试仿真系统,结果表明该仿真系统能够记录被试的信息输入、输出变化的时间及状态,满足显示界面工效研究的需要. 为研究显示界面工效问题提供了一种新手段.     

大型高空台进排气控制半物理仿真系统设计

为构建大型复杂高空模拟试车台进排气控制半物理仿真系统,提出了仿真模型和实物部件相结合的系统设计方法。依据系统结构组成及工作机理统筹规划系统仿真模型和实物部件,利用理论建模、系统辨识方法建立仿真模型,并基于PLC完成系统设计和软件开发,最终将仿真模型和实物部件高效统一形成半物理仿真试验台。通过仿真平台实现了系统一体化虚拟仿真,结果表明系统运行可靠稳定,能够准确模拟真实发动机试车过程。