A FUZZY MATCH BASED EXPERT SYSTEM FOR SYNTHESIS OF SEPARATION PROCESSES

A predictive parallel search algorithm,the fuzzy match inference strategy,is implemented ina prototype expert system.Selection of separation technologies and sequencing of separators are beingapproached in an integrated manner.The fuzzy match mechanism results in a relatively smaller subsetof favored schemes,constituting a hyperstructure for further quantitative evaluation and combinationoptimization.An industrial application example of aromatics extraction separation is presented.     

一个用于化工分离过程合成设计的专家系统

开发了一个基于模糊匹配推理策略的专家系统，可用于分离技术的选择和分离设备的排序。该专家系统首先建立一个可容纳多种设计方案的宏结构，模糊匹配策略驱动一个平行搜索算法，最终产生一集优化的设计方案。     

集成模糊安全评价的反应路径综合

为在过程早期获取本质安全性较好的反应路径,将模糊安全评价集成于反应路径综合形成有效方法。根据反应路径综合阶段信息选择指标,通过设定指标的隶属度函数,建立模糊推理系统,且应用层次分析法（analytic hierarchy process,AHP）求得指标的权重因子,形成了模糊评价方法。为消除中间变量的影响,分别建立单、双输入变量的模糊推理系统。将它集成于反应路径综合,通过原料筛选规则,模糊安全评价,建立以安全为目标的优化模型,求解得到优良的反应路径组合。应用于萘甲胺反应路径综合实例,定量得到了反应路径及其目标函数值,并对两种模糊系统的综合结果进行了比较。     

基于GLSAFIS的氟化工过程操作单元可靠性监测

氟化工产物的剧毒特性,使得对于氟化工过程设备的运行可靠性监控异常重要。为此,提出了基于全局-局部结构分析的模糊推理系统（GLSAFIS）在线评估氟化工过程操作单元运行可靠性。依据氟化工工艺流程选取操作单元过程变量后,通过全局-局部结构分析算法（GLSA）对操作单元过程变量进行全局-局部特征提取。这些低维的全局-局部特征代替原始变量作为模糊推理系统（FIS）的输入,不仅可以克服噪声的影响,降低对专家知识的依赖,同时可以通过特征空间的降维压缩,大大加速后续模糊推理系统的逻辑设计。最后模糊推理系统的实施,使得本方法可以对化工过程操作单元可靠性进行在线评估。国内某氟化工厂二氟一氯甲烷（R-22）生产过程的实际应用以及田纳西伊斯曼模拟过程的仿真结果均证实了所提方法可以准确地反映实际化工过程操作单元的运行状况,大大提高了对实际化工过程的安全监控力度。     

基于模糊逻辑推理的精馏分离序列优化综合

模糊逻辑推理能够反映自然语言要素信息传递特性. 通过抽象有效重组参数提炼if-then模糊逻辑推理规则、根据精馏分离序列综合问题数字特征创建Sugeno模糊逻辑推理模型,系统化地提出了基于模糊逻辑推理的精馏分离序列优化综合方法.     

基于应急演练的化工安全模糊专家系统

在化工安全研究领域中,应用计算机辅助应急预案演练是当今研究的重要方向,其中构建演练专家系统平台是其关键.本文重点分析研究了应急预案演练中的推理技术,获取应急预案中的安全信息及专家知识并加以模糊化,并采用智能混合描述方法实现演练推理机的设计与应用,从而通过精确规则和模糊逻辑规则建立了演练专家系统.通过航煤加氢应急演练案例...     

基于建筑瓷砖烧成缺陷专家系统的模糊推理原型分析

针对建筑瓷砖烧成缺陷诊断问题及其特点,提出了一种基于诊断知识的模糊描述和模糊推理方法,阐述了建筑瓷砖烧成缺陷诊断专家系统中前向推理,后向推理及正反向混合推理模糊断言可信度的计算方法,并给出了相应的实例。     

Prediction of binary azeotrope formation in hydrocarbon mixtures using a knowledge-based expert system

In present study, a hierarchical knowledge-based expert system, named HYDROPERT, to predict binary azeotrope formation in hydrocarbon mixtures was created and investigated. Specific knowledge included in azeotropy on hydrocarbon mixtures and the implementation of the expert system are described along some of the several components of expert system applications: knowledge representation strategy and levels of knowledge abstraction, inference machine, user interface, explanation facilities. The knowledge base is hierarchically structured with the multiple levels of domain-specific knowledge such as the azeotropic data bank as the lowest level, component-specific compiled heuristic rules as the second level, group-oriented compiled heuristic rules as the third level, and generic class-oriented model-based heuristic rules as the highest level. The predictive capabilities and generality of the expert system can be highly enhanced through the integration of different kinds of domain knowledge into the hierarchical structure. The expert system predicting the binary azeotrope formation in hydrocarbon mixtures may be a useful tool for many chemical engineering activities, especially such as process synthesis and design.     

基于模糊HSE评价的多目标反应路径综合方法

为在过程早期获取HSE综合性质优良的反应路径,提出了基于模糊HSE评价的多目标反应路径综合方法。全面考虑HSE因素,形成了HSE指标结构,通过设定指标的隶属度函数,建立模糊推理系统,应用层次分析法（analytic hierarchy process,AHP）确定指标的权重因子,形成了模糊HSE评价方法。基于模糊HSE评价体系,建立以安全、环境和健康为目标函数的多目标优化模型,求解得到优良的反应路径组合。应用于萘甲胺反应路径综合实例,定量得到了反应路径及其HSE目标函数值,为过程早期的路径优选提供定量数据。     

乙烯装置裂解炉智能控制技术

以神经网络、模糊逻辑、专家系统等为代表的一类智能方法在许多领域得到了应用,由于借鉴了人类思维方式、方法,对研究对象先验知识要求少,使用灵活,为解决复杂控制系统的瓶颈提供了崭新的思路和方法。本文针对乙烯生产过程的关键操作单元——裂解炉,阐述了智能控制技术在乙烯装置中的设计思路和实施效果。工业现场的成功应用说明了智能控制技术在过程控制领域具有广阔的应用前景。     

汽轮机组振动故障多征兆模糊诊断专家系统及其应用

利用提取的汽轮机组振动故障的多种征兆 ,并把这些征兆概括为诊断专家系统的知识库 ,用模糊理论建立的模糊方程作为推理规则 ,形成了汽轮机组振动故障多征兆模糊诊断专家系统。通过实际应用检验了该系统的正确性和实用性     

模糊非线性内模控制算法及其在pH值控制中的应用

pH值控制过程具有较强的非线性,历来是过程控制研究的一大热点,本文针对pH值控制系统提出了一种基于模糊推理网的非线性内模控制算法（FNIMC）。模糊推理网用于辨识对象的模糊模型;FNIMC由一个逆模控制器和具有一个可调参数的鲁棒滤波器组成。仿真结果表明该算法优于非线性PID调节器,且计算效率高。     

能量集成蒸馏塔系列的合成

本文分两阶段合成最优热集成蒸馏塔网络:首先优化设计变量使一切可能的热集成产生最大的增益,然后通过合成热集成树在分离顺序空间中找出最小分离成本顺序.由于可行的换热塔对数目不多,而且采用了简捷方法确定最优蒸馏压力,大大减轻了计算量.以一个很通行的例子演示了合成过程.对不同方法合成结果的比较表明新方法对于能量和分离成本均实现了更大幅度的节省.     

基于状态模糊区分专家控制系统的构造与工程实现

在分析热氯化反应过程控制的特点和难点的基础上，提出了专家控制系统的控制策略，对控制目标进行了主次划分和模糊化处理，通过调整状态模糊区分的边界值来改善控制器的性能，设计构造了一个分层的智能专家控制系统，成功应用了工程技术发行并取得了很好的控制效果。     

Model-based reasoning in diagnostic expert systems for chemical process plants

A prototype expert system, called MODEX, for locating the cause(s) of a set of abnormalities in a chemical process id described. We discuss a methodology that aids the developement of expert systems which are process-independent, transparent in their reasoning, and capable of diagnosing a wide diversity of faults. The domain knowlege of the system is based on qualitative reasoning principles and captures physical interconnections between equipment units as well as causal relationships among process state variables. The inference strategy uses model-based reasoning for analyzing the plant behavior. Using a variant of the technique adopted from fault tree synthesis, an initially observed abnormal symptom is considered to be a top level event and a tree structure is constructed as the system searches for a basic event to which the fault can be traced. The diagnostic reasoning process is driven by a problem reduction strategy. The knowledge base is process-independent, thereby enhancing the generality of the expert system. Reasoning from first-principles with the aid of causal and fault models facilitates the diagnoses of novel or unanticipated faults. The system does not assume a single causal origin for all initially observed faults in the chemical process. Moreover, the system has the ability to locate multiple basic causes of a fault. The methodology also permits one to investigate the causal origins of multiple, unrelated, faults. The system provides explanations to user queries at various degrees of detail. Two test cases are discussed in detail.     

DYNAMIC FUZZY ADAPTIVE CONTROLLER FOR pH

Control of pH processes is very difficult due to nonlinear dynamics, high sensitivity at the neutral point, and changes in the concentrations of known or unknown chemical species. In this study, a dynamic fuzzy adaptive controller (DFAC) with a new inference mechanism is proposed and applied for the control of pH processes. The DFAC consists of a low-level basic control phase with a minimum rule base and a high-level dynamic learining phase with an updating mechanism to interact and modify the control rule base. The DFAC can self-adjust its fuzzy control rules using information from the process during on-line control and create new fuzzy control rules or modify the present control rules using its learning capability from past control trends. The controller is evaluated by applying it to a weak acid-strong base pH process with input disturbances and to another pH process that involve that has changes in acidic/buffering streams. The results of the DFAC with the new inference mechanism are compared with the known inference mechanisms, the fuzzy controller, the conventional PI controller, and also with an adaptive PID controller. The proposed DFAC provides better performance for set point tracking of the pH and rejection of load disturbances and buffering affects.     

An expert system for identifying separation processes

This paper presents the development of an expert system, called SIS (Separator Identification System), to generate near-optimal separation sequences for any multicomponent mixture. SIS was designed based on a combination of heuristic and algorithmic approaches. Heuristics were used to select the location of the split. Algorithms were used to calculate physical properties of the multicomponent mixture. A fuzzy approach was used for the propagation of the truth function and uncertainty management. SIS was tested using four sample problems involving gas, liquid, and solid components. The separation sequences suggested by SIS were the same or similar to those found in process synthesis literature.     

Fuzzy Control System in Drying Process of Fermented Sausages

Abstract

Fermented sausages are dried in artificial driers, where the air relative humidity (RH) and temperature (T) are controlled. On the basis of product evaluation, an expert manually readjusts the RH set points in a staggered form. The main drawbacks of this control system are the discontinuity of the product evaluation and the cost of the experts' training. This study proposes a system to readjust the set points of RH based on the theory of fuzzy sets. Two fuzzy control systems were applied to the drying process of fermented sausages in an industrial drier at constant temperature. They used different on-line instrumental measurements related to the expert evaluation as input variables. Results show that fuzzy control can improve the manual control system and it helps quality assurance during the drying process. It reduces the risk of crust development, one of the most serious problems in fermented sausages.