化工过程系统的研究和开发

介绍采用面向对象应用框架法开发的化工过程仿真系统的建模思想和开发过程。抽象的基本模型满足任何化工工艺过程的设备单元 ,保证了模型的通用性。用稳定的抽象设备单元对象和工艺物流对象构成系统的主体框架 ,化工工艺过程中涉及的所有设备和物流实例对象都可以直接或间接从构成系统框架的抽象对象派生。系统具有良好的通用性、稳定性和可扩充性。     

用面向对象的计算机辅助开发环境建立化工培训系统

介绍了基于ＷＩＮＤＯＷＳ的面向对象的新型、高效的计算机辅助开发环境建立化工培训系统,并以硝化甘油生产工艺过程为例具体阐述如何开发化工培训软件。     

用面向对象的计算机辅助开发环境建立化工培训系统

介绍了用基于ＷＩＮＤＯＷＳ的面向对象的新型、高效的计算机辅助开发环境建立化工培训系统,并以硝化甘油生产工艺过程为例具体阐述了如何开发化工培训软件。     

加快发展系统计算机仿真技术

系统计算机仿真技术是近年来开发的一项新技术,一些发达国家应用面向对象的编程技术,对能够建立起系统的数学模型,借助计算机作为工具对系统进行计算机实验研究,可以大大养活实验费用,加快实验进程。我国在系统仿真方面的研究工作已经开始,系统计算机仿真技术将在科学研究,优化生产过程、提高生产效率、保障安全生产等方面发挥有效作用。本期刊登了北京化工大学安亮等撰写的《面向对象的吸收过程动态仿真建模分析》一文,提出了面向对象的通用建模思想,以化工操作单元吸收过程为例,采用面向对象的方法,对现有的主要吸收设备进行分…     

面向对象的输送控制系统编程技术在PCS7上的实现

针对传统顺序控制方案难以满足大规模输送系统中复杂运算要求的问题,提出一种面向对象的输送控制系统控制方法,将系统中设备之间的逻辑关系分别包封在设备、流程和管理器对象中,提出输送系统的三层对象结构,简化了系统的实现过程.根据PCGS7系统的特点,采用消息库的技术实现了对象之间的消息传递,利用PCS7丰富的编程语言实现了面向对象的输送系统.研发结果表明,面向对象技术也可以在DCS系统中实现,具有广阔的应用前景.     

基于对象信息的软件生成技术研究——评《化学化工软件应用教程》

自20世纪80年代以来,面向对象的软件开发生成技术发展迅速并且得到了广泛的应用,在面向对象信息的分析、设计技术以及面向对象信息的程序设计语言方面都有了丰富的研究成果,在当前,面向对象的软件开发方法已经应用的较为普遍。面向对象的方法是一种把面向对象信息应用软件开发的全过程,并在软件开发当中起到指导性作用的方法。《化学化工软件应用教程》对化学化工行业当中需要的各种化学化工工具软件进行了详细的阐述,并将这些软件进行有机结合,便于化学化工专业学生对于化学化工工具软件的掌握和运用。     

面向对象的化工过程动态仿真建模

概述了面向对象技术的特征,提出了一种面向对象的建模框架,并讨论了在动态化工过程中的应用。     

面向对象技术在化工专家系统开发中的应用

面向对象技术近年来获得了很大发展，现已广泛用于数据库、软件工程及人工智能等领域。本文阐述了面向对象技术的基本原理、方法及其优点，介绍了国内外面对对象技术在化工专家系统中应用的概况，着重介绍了在过程能量综合专家系统开发中的应用。     

化工过程运行系统的集成

提出了基于智能体方法的化工过程运行系统的集成策略.依据过程操作响应的时间尺度,把过程运行系统分成故障检测与诊断、模拟优化和调度3个子系统,分别建立相应的智能体模型.通过信息集成和任务集成实现化工过程运行系统的整体集成.报道了该集成方法对TE过程的案例应用.结果表明：基于智能体的方法能实现多个运行决策的全局协调和集成,达到过程运行系统整体优化的目标.     

面向对象方法在化工过程控制系统设计中的应用研究

通过分析传统软件设计方法在化工控制系统软件设计中的不足,从面引入面向对象方法,包括面向对象分析和面向对象设计。在给出计算过程控制基本模型之后,以化工过程控制为例,给出了其中一些对象类的Ｃ＋＋描述。     

Integrated Modelling of Process Operation Systems Using the Agent‐Oriented Approach

For the past years, several software and computer tools have been developed to aid the chemical process operations including real‐time simulation, on‐line optimization, fault diagnosis, process monitoring, and many other functions. These tools were designed separately and did not collaborate efficiently, making it difficult to integrate different engineering tasks for the optimal process operation. In this paper, an agent‐oriented modelling approach is presented to address this problem. Elements in the process operation systems are divided into two classes. One class consists of equipment, units and processes, while the other class consists of production operation tasks. The two classes of elements are modelled as objects and agents, respectively. Then, three strategies are presented to implement the integration of the whole process operation system, which are integration of object models, integration of agent models and supervision of operator. Also presented is a case study of integration of process operation decision optimization and abnormal situation management using the proposed agent oriented approach for TE challenge problem.     

ARTIFICIAL NEURAL NETWORKS: PRINCIPLE AND APPLICATION TO MODEL BASED CONTROL OF DRYING SYSTEMS - A REVIEW

This paper reviews the developments in the model based control of drying systems using Artificial Neural Networks (ANNs). Survey of current research works reveals the growing interest in the application of ANN in modeling and control of non-linear, dynamic and time-variant systems. Over 115 articles published in this area are reviewed. All landmark papers are systematically classified in chronological order, in three distinct categories; namely, conventional feedback controllers, model based controllers using conventional methods and model based controllers using ANN for drying process. The principles of ANN are presented in detail. The problems and issues of the drying system and the features of various ANN models are dealt with upto-date. ANN based controllers lead to smoother controller outputs, which would increase actuator life. The paper concludes with suggestions for improving the existing modeling techniques as applied to predicting the performance characteristics of dryers. The hybridization techniques, namely, neural with fuzzy logic and genetic algorithms, presented, provide, directions for pursuing further research for the implementation of appropriate control strategies. The authors opine that the information presented here would be highly beneficial for pursuing research in modeling and control of drying process using ANN     

ARTIFICIAL NEURAL NETWORKS: PRINCIPLE AND APPLICATION TO MODEL BASED CONTROL OF DRYING SYSTEMS - A REVIEW

Abstract

This paper reviews the developments in the model based control of drying systems using Artificial Neural Networks (ANNs). Survey of current research works reveals the growing interest in the application of ANN in modeling and control of non-linear, dynamic and time-variant systems. Over 115 articles published in this area are reviewed. All landmark papers are systematically classified in chronological order, in three distinct categories; namely, conventional feedback controllers, model based controllers using conventional methods and model based controllers using ANN for drying process. The principles of ANN are presented in detail. The problems and issues of the drying system and the features of various ANN models are dealt with upto-date. ANN based controllers lead to smoother controller outputs, which would increase actuator life. The paper concludes with suggestions for improving the existing modeling techniques as applied to predicting the performance characteristics of dryers. The hybridization techniques, namely, neural with fuzzy logic and genetic algorithms, presented, provide, directions for pursuing further research for the implementation of appropriate control strategies. The authors opine that the information presented here would be highly beneficial for pursuing research in modeling and control of drying process using ANN     

Organizational and technological modeling of chemical process systems

A method was suggested for modeling the chemical process systems using the business process models based on SADT, which takes into account the fixed technological structure of chemical process objects.     

Process systems engineering tools in the pharmaceutical industry

The purpose of this paper is to provide a summary of the current state of the application of process systems engineering tools in the pharmaceutical industry. In this paper, we present the compiled results of an industrial questionnaire submitted to pharmaceutical industry professionals. The topics covered in the questionnaire include process analytics, process monitoring, plant-wide information systems, unit operation modeling, quality control, and process optimization. A futuristic view of what process systems engineering tools will enable the pharmaceutical industry will be also be presented. While the industry is regularly using the traditional Design of Experiments approach to identify key parameters and to define control spaces, these approaches result in passive control strategies that do not attempt to compensate for disturbances. Special new approaches are needed for batch processes due to their essential dependence on time-varying conditions. Lastly, we briefly describe a novel data driven modeling approach, called Design of Dynamic Experiments that enables the optimization of batch processes with respect to time-varying conditions through an example of a simulated chemical reaction process. Many more approaches of this type are needed for the calculation of the design and control spaces of the process, and the effective design of feedback systems.     

Rechnergestützte Erstellung verfahrenstechnischer Prozeßmodelle

Computer-aided generation of chemical engineering process models. The availability of adequate process models is still the most striking bottleneck for routine application of model-based techniques in process design and operation. The development of knowledge-based software tools to support process modeling is considered an important contribution to a solution of this problem. After a brief summary of the modeling tools offered in current simulator architectures, a future knowledge-based modeling tool is sketched. In addition to the software engineering, the acquisition and formalization of the modeling knowledge – comprising meaningful submodels and generic modeling strategies – is essential for the feasibility of the approach and for the acceptance of a tool. Therefore, these two themes are discussed in considerable detail. Finally, first prototype developments towards a knowledge-based modeling tool are presented.     

PLS回归软测量方法在催化重整稳定油组分估计中的应用

提出扰动分类法和线性部分最小二乘（PLS）回归相结合的建立软测量模型的方法，并将它用于催化重整稳定油组分的估计中。仿真结果表明扰动分类法和PLS回归相结合建立的软测量模型简单、实用。     

Design and optimization of hydrogen storage units using advanced solid materials: General mathematical framework and recent developments

This review presents the general mathematical framework of modeling, design and optimization of hydrogen storage using advanced solid materials. The emphasis is given on metal hydride storage tanks, since these systems have been well studied in the literature, both theoretically and experimentally, and are expected to offer significant advantages when current research and development efforts succeed in commercializing the required technology. Enhanced cooling during hydrogen filling of the storage tank is found to be essential to improve hydrogen storage time requirements. For this reason several innovative design strategies for heat exchanger configurations are presented and evaluated in terms of process design and performance improvement. Finally, control and optimization of certain operating conditions can also have a significant impact in hydrogen storage operation.     

基于智能体的石化智能工厂信息物理系统实现研究

结合石化行业的特点与石化信息物理系统已有研究成果,提出了一种基于智能体（agent）的信息物理系统的构建方法。以石化主要生产领域涉及的物理对象和度量对象,以及这些要素相互关系为核心建立的工厂模型为基础,将具有感知和响应能力的智能体应用于企业工厂模型工作节点,使得工厂模型对象具有计算、预测、知识学习能力,实现基于智能体的智能分析、预测预警、生产监测以及可视化的石化信息物理系统。描述了工厂模型构建方法、基于工厂模型的智能体工作模式以及基于智能体的石化智能工厂信息物理系统架构,并通过展示中国石化智能工厂试点企业应用实践,论证该方法的实用效果。