可拓理论在过程工业中的应用研究
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摘要
近年来,过程工业生产规模不断扩大,生产过程日趋复杂多变,传统的工业应用技术逐渐难以满足实际生产运行的需求。因此,如何进一步研究生产过程中现代自动化技术,更好地确保生产安全、保证产品质量以及提高生产效益成为人们关注的焦点。
可拓理论是一门新兴的原创性学科,其采用形式化的模型探讨事物拓展的可能性及开拓创新的规律与方法,以基元理论、可拓集理论和可拓逻辑为理论核心,通过可拓分析、可拓变换、可拓推理等形成解决矛盾问题策略的有效方法。由此,本文针对工业生产中的过程建模变量选择、报警监控系统管理及操作调节方案设计等问题,在传统工业应用技术基础上,结合可拓理论,提出了过程建模变量可拓选择方法、过程报警监控系统可拓管理方法及过程操作调节可拓方案设计方法,并实现了其在精对苯二甲酸溶剂系统和高密度聚乙烯串级聚合反应过程中的具体工业生产应用。
本文研究内容如下：
为更好的进行过程模拟及预测,针对过程模型化研究中变量选择问题,采用基元模型统一化描述过程变量,运用基元模型的可拓性及其变换方法研究过程变量间的可拓性问题,并通过改进权重算法判断过程变量重要性,最终实现过程建模变量可拓选择。
随着生产安全要求的不断提高,报警监控系统管理越发重要,采用基元模型构建报警监控可拓体系,运用关联函数定量化报警监控参数与系统状态间关系,并通过改进权重算法计算报警监控参数权重,最终实现报警监控系统可拓管理。
针对过程工业中节能降耗问题,对操作调节进行方案设计,采用基元模型进行可拓方案描述,运用基元模型的可拓性及其变换方法拓展操作调节方案,结合可拓评价方法及改进权重算法选取最佳调节方案,最终实现操作调节可拓方案设计。
为验证过程建模变量可拓选择方法、报警监控系统可拓管理方法及操作调节可拓方案设计方法的可行性及有效性,将其分别应用于中石化某分公司PTA溶剂系统及中石油某分公司HDPE串级聚合反应过程中,用于解决具体生产过程建模变量选择、报警监控管理以及操作调节方案设计等问题。
本课题创新之处在于将可拓理论中的基元模型描述引入到过程系统工程领域,将基元模型可拓性及其变换方法、关联函数可拓关系构建与可拓评价方法分别有效地融于过程建模变量选择、报警监控管理及操作调节方案设计中并实现了具体生产过程应用,同时针对实际需求对相关理论进行了创新和改进,使其更能适应实际的需要,为实现现代化工业生产过程模拟、决策及优化控制提供了新途径。
Recently, with the continuously enlarging plant scale, production process is becoming more complex and changeable, gradually traditional technology of industry application can not satisfy the need of actual production running. Therefore, great concern has been focused on how to further make research on modern automation technology in production process to guarantee the product quality, enhance the production benefit and ensure the production safety.
Extension theory is an original subject, which applies the formal model to expand the possibility of matter and explore the innovative principle. It takes the element theory, extension set and extension logic as the core, and solves the contradiction problems by extension analysis, extension transformation and extension reasoning. Therefore, in the paper, based on the traditional technology of industry application, further research is made on the variable selection of process modeling, system management of alarm monitoring, and scheme design of operating regulation for industry production by combining the extension theory, which are the extension selection for modeling variables, extension management for alarm monitoring, and extension scheme design for operating regulation. Also, actual industry applications are realized successfully in purified terephthalic acid solvent system and high-density polyethylene cascade polyreaction process.
The main research contents are as follows:
For better process simulation and prediction, aiming at the variable selection in process modeling, the element-model is used to describe the process variables, the extension nature and transformation methods are applied to study the extension problem during the process variables, the improvement for weight algorithm is made to judge the importance of process variables, and finally the extension selection for modeling variables is realized.
With the increasing requirement for production safety, the management for alarm monitoring is becoming more important. The element-model is used to establish the alarm monitoring system, the correlation function is applied to quantify the relation between the alarm monitoring parameters and the system condition, the improvement for weight algorithm is made to calculate the weight of each alarm monitoring parameter, and finally the extension management for alarm monitoring system is realized.
Aiming at the problem of energy saving and consumption lowering in process industry, the scheme design for operating regulation is needed. The element-model is used to describe the extension scheme, the extension nature and transformation method is applied to extend the schemes for operating regulation, the extension evaluation and improved weight algorithm are combined for the optimal selection of regulation schemes, and finally the extension scheme design for operating regulation is realized.
In order to prove the feasibility and validity of the proposed extension selection for modeling variables, extension management for alarm monitoring system and extension scheme design for operating regulation, the industry applications are made in PTA solvent system of a Petrochemical Corporation and HDPE cascade polyreaction process of a Petroleum Corporation to solve the selection for modeling variables, management for alarm monitoring system and scheme design for operating regulation.
The innovations of this work are as follows:introducing extension-element into the area of process system engineering, combining the extension nature and transformation methods, the extension relation establishment by the correlation function and extension evaluation method to the variable selection of process modeling, the management for alarm monitoring and the scheme design for operating regulation, respectively, and realizing the process applications for actual productions. Also, some innovations and improvements are made when using the extension theory so as to satisfy the actual need, which provide new ways to process simulation, decision making and optimization control for modern industry production.
可拓理论是一门新兴的原创性学科,其采用形式化的模型探讨事物拓展的可能性及开拓创新的规律与方法,以基元理论、可拓集理论和可拓逻辑为理论核心,通过可拓分析、可拓变换、可拓推理等形成解决矛盾问题策略的有效方法。由此,本文针对工业生产中的过程建模变量选择、报警监控系统管理及操作调节方案设计等问题,在传统工业应用技术基础上,结合可拓理论,提出了过程建模变量可拓选择方法、过程报警监控系统可拓管理方法及过程操作调节可拓方案设计方法,并实现了其在精对苯二甲酸溶剂系统和高密度聚乙烯串级聚合反应过程中的具体工业生产应用。
本文研究内容如下：
为更好的进行过程模拟及预测,针对过程模型化研究中变量选择问题,采用基元模型统一化描述过程变量,运用基元模型的可拓性及其变换方法研究过程变量间的可拓性问题,并通过改进权重算法判断过程变量重要性,最终实现过程建模变量可拓选择。
随着生产安全要求的不断提高,报警监控系统管理越发重要,采用基元模型构建报警监控可拓体系,运用关联函数定量化报警监控参数与系统状态间关系,并通过改进权重算法计算报警监控参数权重,最终实现报警监控系统可拓管理。
针对过程工业中节能降耗问题,对操作调节进行方案设计,采用基元模型进行可拓方案描述,运用基元模型的可拓性及其变换方法拓展操作调节方案,结合可拓评价方法及改进权重算法选取最佳调节方案,最终实现操作调节可拓方案设计。
为验证过程建模变量可拓选择方法、报警监控系统可拓管理方法及操作调节可拓方案设计方法的可行性及有效性,将其分别应用于中石化某分公司PTA溶剂系统及中石油某分公司HDPE串级聚合反应过程中,用于解决具体生产过程建模变量选择、报警监控管理以及操作调节方案设计等问题。
本课题创新之处在于将可拓理论中的基元模型描述引入到过程系统工程领域,将基元模型可拓性及其变换方法、关联函数可拓关系构建与可拓评价方法分别有效地融于过程建模变量选择、报警监控管理及操作调节方案设计中并实现了具体生产过程应用,同时针对实际需求对相关理论进行了创新和改进,使其更能适应实际的需要,为实现现代化工业生产过程模拟、决策及优化控制提供了新途径。
Recently, with the continuously enlarging plant scale, production process is becoming more complex and changeable, gradually traditional technology of industry application can not satisfy the need of actual production running. Therefore, great concern has been focused on how to further make research on modern automation technology in production process to guarantee the product quality, enhance the production benefit and ensure the production safety.
Extension theory is an original subject, which applies the formal model to expand the possibility of matter and explore the innovative principle. It takes the element theory, extension set and extension logic as the core, and solves the contradiction problems by extension analysis, extension transformation and extension reasoning. Therefore, in the paper, based on the traditional technology of industry application, further research is made on the variable selection of process modeling, system management of alarm monitoring, and scheme design of operating regulation for industry production by combining the extension theory, which are the extension selection for modeling variables, extension management for alarm monitoring, and extension scheme design for operating regulation. Also, actual industry applications are realized successfully in purified terephthalic acid solvent system and high-density polyethylene cascade polyreaction process.
The main research contents are as follows:
For better process simulation and prediction, aiming at the variable selection in process modeling, the element-model is used to describe the process variables, the extension nature and transformation methods are applied to study the extension problem during the process variables, the improvement for weight algorithm is made to judge the importance of process variables, and finally the extension selection for modeling variables is realized.
With the increasing requirement for production safety, the management for alarm monitoring is becoming more important. The element-model is used to establish the alarm monitoring system, the correlation function is applied to quantify the relation between the alarm monitoring parameters and the system condition, the improvement for weight algorithm is made to calculate the weight of each alarm monitoring parameter, and finally the extension management for alarm monitoring system is realized.
Aiming at the problem of energy saving and consumption lowering in process industry, the scheme design for operating regulation is needed. The element-model is used to describe the extension scheme, the extension nature and transformation method is applied to extend the schemes for operating regulation, the extension evaluation and improved weight algorithm are combined for the optimal selection of regulation schemes, and finally the extension scheme design for operating regulation is realized.
In order to prove the feasibility and validity of the proposed extension selection for modeling variables, extension management for alarm monitoring system and extension scheme design for operating regulation, the industry applications are made in PTA solvent system of a Petrochemical Corporation and HDPE cascade polyreaction process of a Petroleum Corporation to solve the selection for modeling variables, management for alarm monitoring system and scheme design for operating regulation.
The innovations of this work are as follows:introducing extension-element into the area of process system engineering, combining the extension nature and transformation methods, the extension relation establishment by the correlation function and extension evaluation method to the variable selection of process modeling, the management for alarm monitoring and the scheme design for operating regulation, respectively, and realizing the process applications for actual productions. Also, some innovations and improvements are made when using the extension theory so as to satisfy the actual need, which provide new ways to process simulation, decision making and optimization control for modern industry production.
引文
[1]David K.W.Ng and Cai Wen. Treating Non-compatible Problem from Matter element Analysis to Extenics[J]. ACM SIGICE Bulletin,1997,22(3):1-9.
[2]Wen Cai. Extension Management Engineering and Applications[J]. International Journal of Operations and Quantitative Management,1999,5(1):59-72.
[3]Ruzhong Li, Tianqiu Hong, Jiazhong Qian. Information Entropy Fuzzy Matter-element Model and Its Application to Regional Eco-environmental Quality Assessment[J]. Journal of Systems Science and Information,2006,4(41):649-659.
[4]Yang Guowei, Zhang Fusheng, Tu Xuyan. Decision Making Based on Extension Models of Innovative and Creative Thinking[J]. Measurement and Control D,2003,24(2):1-17.
[5]Chen Zhengyuan, Wang Qingchang. A Simple PI Extension Controlle[J]. Journal of Guangdong University of Technology,2001,18(1):38-41.
[6]徐顺喜,王行愚.连续生产综合自动化系统功能集成的可拓控制模型[J].系统工程理论与实践,1998,2：110-113.
[7]潘东,金以慧.可拓控制的探索与研究[J].控制理论与应用,1996,13(3)：305-311.
[8]何斌,朱学峰.可拓自适应混杂控制[J].控制理论与应用,2005,22(2)：165-170.
[9]卢荣德,陈宗海.基于可拓论的工业水分过程系统综合建模[J].系统仿真学报,2003,6(15)：783-787.
[10]朱群雄,顾祥柏.基于物元的流程工业MES信息表示与信息维模型应用[J].计算机与应用化学,2005,22(8)：671-677.
[11]朱群雄,宣达婧.基于可拓论的信息仓库建模[J].计算机与应用化学,2006,23(1)：73-76.
[12]顾祥柏,朱群雄,宣达婧.物元全信息测度算法实现及其应用[J].石油化L高等学校学报,2005,18(3)：75-78.
[13]顾祥柏,朱群雄.基于物元的流程报警系统重构算法及应用[J].控制与决策,2005,20(9)：1006-1011.
[14]W.C.Zhu, C.A.Tang. Numerical Simulation on Shear Fracture Process of Concrete Using Mesoscopic Mechanical Model[J]. Construction and Building Materials,2002,16: 453-463.
[15]Venkat Venkatasubramanian, Raghunathan Rengaswamy, Kewen Yin, Surya N.Kavuri. A Review of Process Fault Detection and Diagnosis:Part Ⅰ:Quantitative Model-based Methods[J]. Computers & Chemical Engineering,2003,27:293-311.
[16]Wu Min, Nakano Micho, She Jin-Hua. A Distributed Expert Control System for a Hydrometallurgical Zinc Process[J]. Control Engineering Practice,1998,6:1435-1446.
[17]Radhakrishnan V.R., Mahamed A.R.. Neural Networks for the Identification and Control of Blast Furnace Hot Metal Quality[J]. Journal of Process Control,2000,10(6):509-524.
[18]Babuska R, Verbruggon H B, Vancan H J L. Fuzzy Modeling of Enzymatic penicillin-G Anversion[J]. Engineering Application of Artificial Intelligence,1999,12(1):79-92.
[19]熊智华,王雄,徐用懋.一种利用多神经网络结构建立非线性软测量模型的方法[J].控制与决策,2000,15(2)：173-176.
[20]王旭东,邵惠鹤,罗荣富.分布式RBF神经网络及其在软测量方面的作用[J].控制理论与应用,1998,15(4)：558-563.
[21]王旭东,邵惠鹤.基于神经网络的通用软测量技术[J].自动化学报,1998,24(5)：702-706.
[22]王宏伦,终明安,戴冠中.基于分类／组合的模糊神经元网络[J].信息与控制,1999,28(7)：693-696.
[23]程华农,钱宇,李秀喜,李荷华,江燕斌.化工过程系统集成建模的面向智能体方法[J].化工学报,2003,54(1)：128-130
[24]Cho S Z, Cho Y J, Yoon S C. Reliable Roll Force Prediction in Cold Mill Using Multiple Neural Networks[J]. IEEE Tran. Neural Networks.1997,8(4):874-880.
[25]黄道平,朱学峰,周其节.基丁一种集成模型的多变量非线性预测控制[J].控制理论与应用,1999,16(1)：38-42.
[26]秦秀娟,陈宗海.汽油辛烷值神经网络预测模型的设计[J].控制与决策,1999,14(2)：151-155.
[27]Wang Y, Rong G. A Self-organizing Neural-network-based Fuzzy System[J]. Fuzzy Sets and Systems,1999,103:1-11.
[28]吴建峰,何小荣,陈丙珍.一种用于动态化工过程建模的反馈神经网络新结构[J].化工学报,2002,53(2)：156-160.
[29]Detlef N, Kruse R. Neural-fuzzy Systems for Function Approximation[J]. Fuzzy Sets and Systems,1999,101:261-271.
[30]Grosdidier P, Connor P, Hollifield B, Kulkarni S. A Path forward for DCS Alarm Management[J]. Hydrocarbon Processing,2003, November:59-64.
[31]Brown N. Effective Alarm Management[J]. Hydrocarbon Processing,2004, January: 68-71.
[32]Chao C S, Liu A C. An Alarm Management Framework for Automated Network Fault Identification[J]. Computer Communications,2004,27(13):1341-1353.
[33]J.de Wit. EEMUA Recommendations for the Design and Construction of Refrigerated Liquefied Gas Storage Tanks [J]. Cryogenics,1998,28(12):800-804.
[34]Domijan P, Kalpic D. Off-line Energy Optimization Model for Crude Distillation Unit[J]. Industrial Electronics.2005,1:199-204.
[35]Coca D. Review of Results and Perspectives of Nonlinear Process Identification from Experimental Data[J]. Space Res.,2003,32(3):331-345.
[36]Nakaiwa M., Huang K., Naito K.. Parameter Analysis and Optimization of Ideal Heat Integrated Distillation Columns[J]. Computers and Chemical Engineering,2001,25: 737-744.
[37]Low K.H., Sorensen E.. Simultaneous Optimal Configuration, Design and Operation of Batch Distillation[J]. AICHE Journal,2005,51(6):1700-1713.
[38]Bhaskar V., Gupta S.K., Ray A.K.. Multiobjective Optimization of an Industrial Wiped Film Poly (Ethylene Terephthalate) Reactor:Some further Insights[J]. Computers and Chemical Engineering,2001,25:391-407.
[39]Bhaskar V., Gupta S.K., Ray A.K.. Multiobjective Optimization of an Industrial Wiped-Film Pet Reactor[J]. AICHE Journal,2000,46(5):1046-1058.
[40]Kasat R.B., Kunzru D., Saraf D.N., Gupta S.K.. Multiobjective Optimization of Industrial FCC Units Using Elitist Nondominated Sorting Genetic Algorithm[J]. Ind.Eng.Chem.Res., 2002,41(19),4765-4776.
[41]Rajesh J.K., Gupta S.K., Rangaiah G.P., Ray A.K.. Multi-objective Optimization of Industrial Hydrogen Plants[J]. Chemical Engineering Science,2001,56(3):999-1010.
[42]Cai Wen. Extension theory and its application[J]. Chinese Science Bulletin,1999,44(17): 1538-1548.
[43]Cai Wen, Yang Chunyan, Lin Weichu. Extension Engineering Methods[M]. Beijing: Science Press,2003.
[44]Guowei Yang. Intelligentized and Modeling Conceptual Design Based on the Analysis of Matter Element Dynamic System[J]. Computer Engineering and Applications,2005, 41(16):109-113.
[45]王广鹏,赵燕伟.面向可拓知识集成的创新设计系统研究[J].机电工程,2003,10：132-132.
[46]向阳,于长锐.基于知识的规划模型构造系统研究[J].系统工程学报,2002,17(1)：72-77.
[47]胡宝清.区域水环境质量的区间可拓评价方法及应用[J].中国工程科学,2001,3(6)：53-56.
[48]戴琳.可拓学在工程质量评定中应用的研究[J].南京师范大学学报(工程技术版),2002,2(3)：21-25.
[49]赵燕伟,张国贤.可拓故障诊断方法及其应用[J].机械工程学报,2001,37(9)：39-43.
[50]黄文涛,赵学增,王伟杰.基于物元模型的电力变压器故障的可拓诊断方法[J].电力系统自动化,2004,28(13)：45-49.
[51]王万良,吴刚.分层多变量可拓控制器及其应用[J].广东工业大学学报,1999,16(4)：102-105.
[52]阳林,吴黎明,黄爱华.可拓控制的物元模型及其控制算法[J].系统工程理论与实践,2000,20(6)：126-130.
[53]车录锋,周晓军,徐志农,程耀东.可拓方法在多传感器信息融合工件识别中的应用[J].系统工程理论与实践,2000,8：91-94.
[54]龚京忠,邱静,李国喜,李伟.产品模块可拓变型设计方法[J].计算机集成制造系统,2008,14(7)：1256-1267.
[55]楼健人,伊国栋,张树有,谭建荣.基于知识的产品可拓配置与进化设计技术研究[J].浙江大学学报(工学版),2007,41(3)：466-470.
[56]苏楠,赵燕伟,唐辉军,赵富贵,张峰,桂元坤.基于可拓逻辑的产品族可配置规划研究[J].计算机集成制造系统,2008,14(10)：1897-1903.
[57]周鸣争,杨益民.菱形思维的可拓神经网络实现[J].系统工程理论与实践,2000,6：121-124
[58]王鸿洁,常国岑.可拓神经网络在可拓专家系统中的研究与应用[J].系统L程与电子技术,2005,27(2)：264-266
[59]孙佰清,刑爱国,张积宾,潘启树.可拓神经网络模型的设计与实现[J].哈尔滨工业大学学报,2006,38(7)：1157-1159.
[60]郑鑫,秦建军,陈汉辉,李伟宏.基于可拓学的自然语言处理与系统建模研究[J].哈尔滨工业大学学报,2006,38：1209-1212.
[61]卢荣德,陈宗海,王雷.思维模拟在复杂工业过程建模中应用的综述[J].信息与控制,2002,4(31)：346-352.
[62]蔡文,杨春燕,林伟初.可拓工程方法[M].北京：科学出版社,1997.
[63]杨春燕.事元及其应用[J].系统工程理论与实践,1998,2：80-86.
[64]杨春燕,蔡文.可拓工程研究[J].中国工程科学,2000,2(12)：90-96.
[65]李立希,李嘉.可拓知识库系统及其应用[J].中国工程科学,2001,3(3)：61-64.
[66]蔡文,杨春燕,何斌.可拓逻辑初步[M].北京：科学出版社,2003.
[67]杨春燕,张拥军,蔡文.可拓集合及其应用研究[J].数学实践与认识,2002,32(2)：301-303.
[68]胡宝清.区间上的可拓集及其关联函数[J].广东工业大学学报,2000,17(2)：101-04.
[69]高洁,谢敬东.基于关联函数的变压器故障可拓诊断方法[J].系统工程,2000,18(5)：64-69.
[70]高洁,戴建新,王雪红.可拓决策方法综述[J].系统工程理论方法应用,2004,13(3)：264-271.
[71]李立希,杨春燕,李铧汶.可拓策略生成系统[M].北京：科学出版社,2006.
[72]Mu Shengjing, Su Hongye, Gu Yong, Chu Jian. Multi-objective Optimization of Industrial Purified Terephthalic Acid Oxidation Process[J]. Chinese J. Chem. Eng.,2003,11(5): 536-541.
[73]Dorn, C., Morari, M.. Qualitative Analysis for Homogenous Azeotropic Distillation.1. Local Stability[J]. Ind. Eng. Chem. Res.,2002,41(16):3930-3942.
[74]Weiyang Cheong, Paul I Barton. Azeotropic Distillation in a Middle Vessel Batch Column.3.Model Validation[J]. Ind. Eng.Chem. Res.,1999,38:1549-1564.
[75]Chien, I.L., Wang, C.J., Wong, D.S.H.. Dynamics and Control of a Heterogeneous Azeotropic Distillation Column:Conventional Control Approach[J]. Ind. Eng. Chem. Res.,1999,38:468-478.
[76]Guo, Z., Chin, J., Lee, J.W.. Feasibility of Continuous Reactive Distillation with Azeotropic Mixtures[J]. Ind. Eng. Chem. Res.,2004,43:3758-3769.
[77]Feng, G.Y., Fan, L.T., Seib, P.A., Bertok, B., Kalotai, L., Friedler, F.. Graph-Theoretic Method for the Algorithmic Synthesis of Azeotropic-Distillation System[J]. Ind. Eng. Chem. Res.,2003,42:3602-3611.
[78]Eleonora Bonanomi, Manfred Morari, Phase-Plane Analysis of Homogeneous Azeotropic Distillation Columns[J]. Ind. Eng. Chem. Res.,2002,41:3963-3969.
[79]J.F. Mastral, C. Berrueco, J. Ceamanos. Modeling of the Pyrolysis of High Density Polyethylene Product Distribution in a Fluidized Bed Reactor[J]. J. Anal. Appl. Pyrolysis, 2007,79:313-322.
[80]杨晓梅,华贲,李国庆.低压高密度聚乙烯装置反应系统模型开发[J].计算机与应用化学,2004,21(1)：127-131.
[8l]王淑清.低压高密度聚乙烯装置动态模拟模型开发策略浅谈[J].现代化工,2003,23(3)：44-47.
[82]Yuan XU, Qunxiong ZHU. Extension Theory-based Modeling for Purified Terephthalic Acid Solvent System[A]. The 8th IEEE International Conference on Control & Automation,2010, Xiamen, China.
[83]Yuan XU, Qunxiong ZHU. A New Process Modeling Method Based on Extension Theory and Its Application in Purified Terephthalic Acid Solvent System[A]. The 20th International Conference on Multiple Criteria Decision Making (MCDM2009),2009, 154-157, Chengdu, China.
[84]Ling Wang, Jian Chu, Jun Wu. Selection of Optimum Maintenance Strategies Based on Fuzzy Analytic Hierarchy Process[J]. International Journal of Production Economics, 2007,107(1):151-163.
[85]E.H.Forman, S.I.Gass. The Analytic Hierarchy Process-An Exposition[J]. Operations Research,2001,49(4):469-486.
[86]Athanasios I. Chatzimouratidis, Petros A.Pilavachi. Multicriteria Evaluation of Power Plants Impact on the Living Standard Using the Analytic Hierarchy Process[J]. Energy Policy,2008,36(3):468-478.
[87]Willis.M.J., Di Massimo.C., Montague.G.A., Tham.M.T., Morris.A.J.. Artificial Neural Networks in Process Engineering[J]. IEE Proceedings-D,1991,138(3):256-266.
[88]Wang Weibin, Zheng Pi'e, Li Jinyong. Application of BP NN and RBF NN in Modeling Activated Sludge System [J]. Transaction of Tianjin University.2003,9(3):235-240.
[89]Weixiang Zhao, Dezhao Chen, Shangxu Hu. Detection of Outlier and a Robust BP Algorithm against Outlier[J]. Computers and Chemical Engineering,2004,28:1403-1408.
[90]A.T.C.Goh. Back-propagation Neural Networks for Modeling Complex Systems[J]. Artificial Intelligence in Engineering,1995,9:143-151.
[91]B.H.M.Sadeghi. A BP-neural Network Predictor Model for Plastic Injection Molding Process[J]. Journal of Materials Processing Technology,2000,103(3):411-416.
[92]Specht, D.F.. A General Regression Neural Network[J]. IEEE Transactions on Neural Networks,1991,2 (6):258-276.
[93]Li, Z.W., Sun, J.Z., ZHANG, Z.Q.. Reconstruction of Novel Viewpoint Image Using GRNN[J]. Transactions of Tianjin University,2003,2 (9):136-139.
[94]Mark T.Leung, An-Sing Chen, Hazem Daouk. Forecasting Exchange Rates Using General Regression Neural Networks[J]. Computers and Operations Research,2000,27(11): 1093-1110.
[95]Masters.T, Land.W.. A New Training Algorithm for the General Regression Neural Network[A]. IEEE International Conference on Systems, Man, and Cybernetics,1997,3: 1990-1194.
[96]Yuan XU, Qunxiong ZHU. Research and Implementation of Decreasing the Acetic Acid Consumption in Purified Terephthalic Acid Solvent System[J]. Chinese Journal of Chemical Engineering,2008,16 (4):650-655.
[97]Zhang Jian,Kang Jingli,Wang Minnan. A RBF Network Based Nonlinear Modeling of Diesel Engine[J]. Transaction of CSICE.2003,21(3):221-226.
[98]Ying Tan, Jun Wwang, Jacek M.Zurada. Nonlinear Blind Source Separation Using a Radial Basis Function Network[J]. IEEE Transactions on Neural Networks,2001,12(1): 124-134.
[99]D.L.Yu, J.B.Gomm, D.Williams. Sensor Fault Diagnosis in a Chemical Process via RBF Neural Networks[J]. Control Engineering Practice,1999,7(1):49-55.
[100]Yuan XU, Qunxiong ZHU. A New Method for Monitoring Management in Chemical Process[A]. The 1st International Conference on Information Science and Engineering (ICISE2009),2009, Nanjing, China.
[101]徐圆,朱群雄.基于物元分析的过程工业报警优化[J].化工学报,2008,59(7)：1609-1614.
[102]徐圆,朱群雄.可拓理论在流程工业中的应用[J].控制工程,2008,15(3)：283-286.
[103]Yuan XU, Qunxiong ZHU. A New Design Method for Energy Saving and Consumption Reducing of Process Industry Based on Extension Theory[J]. International Journal of Innovative Computing, Information and Control,2010,6 (5).
[104]Yuan XU, Qunxiong ZHU. Scheme Design for Energy Saving and Consumption Lowing of Process Industry Based on Extension Theory [A]. The 3nd International Symposium on Computational Intelligence and Industrial Applications (ISCIIA 2008),2008,435-443, Dali, China.
[105]徐圆,朱群雄.基于可拓理论的过程工业智能操作优化方法及应用[J].化工学报,2009,60(10)：126-132.
[2]Wen Cai. Extension Management Engineering and Applications[J]. International Journal of Operations and Quantitative Management,1999,5(1):59-72.
[3]Ruzhong Li, Tianqiu Hong, Jiazhong Qian. Information Entropy Fuzzy Matter-element Model and Its Application to Regional Eco-environmental Quality Assessment[J]. Journal of Systems Science and Information,2006,4(41):649-659.
[4]Yang Guowei, Zhang Fusheng, Tu Xuyan. Decision Making Based on Extension Models of Innovative and Creative Thinking[J]. Measurement and Control D,2003,24(2):1-17.
[5]Chen Zhengyuan, Wang Qingchang. A Simple PI Extension Controlle[J]. Journal of Guangdong University of Technology,2001,18(1):38-41.
[6]徐顺喜,王行愚.连续生产综合自动化系统功能集成的可拓控制模型[J].系统工程理论与实践,1998,2：110-113.
[7]潘东,金以慧.可拓控制的探索与研究[J].控制理论与应用,1996,13(3)：305-311.
[8]何斌,朱学峰.可拓自适应混杂控制[J].控制理论与应用,2005,22(2)：165-170.
[9]卢荣德,陈宗海.基于可拓论的工业水分过程系统综合建模[J].系统仿真学报,2003,6(15)：783-787.
[10]朱群雄,顾祥柏.基于物元的流程工业MES信息表示与信息维模型应用[J].计算机与应用化学,2005,22(8)：671-677.
[11]朱群雄,宣达婧.基于可拓论的信息仓库建模[J].计算机与应用化学,2006,23(1)：73-76.
[12]顾祥柏,朱群雄,宣达婧.物元全信息测度算法实现及其应用[J].石油化L高等学校学报,2005,18(3)：75-78.
[13]顾祥柏,朱群雄.基于物元的流程报警系统重构算法及应用[J].控制与决策,2005,20(9)：1006-1011.
[14]W.C.Zhu, C.A.Tang. Numerical Simulation on Shear Fracture Process of Concrete Using Mesoscopic Mechanical Model[J]. Construction and Building Materials,2002,16: 453-463.
[15]Venkat Venkatasubramanian, Raghunathan Rengaswamy, Kewen Yin, Surya N.Kavuri. A Review of Process Fault Detection and Diagnosis:Part Ⅰ:Quantitative Model-based Methods[J]. Computers & Chemical Engineering,2003,27:293-311.
[16]Wu Min, Nakano Micho, She Jin-Hua. A Distributed Expert Control System for a Hydrometallurgical Zinc Process[J]. Control Engineering Practice,1998,6:1435-1446.
[17]Radhakrishnan V.R., Mahamed A.R.. Neural Networks for the Identification and Control of Blast Furnace Hot Metal Quality[J]. Journal of Process Control,2000,10(6):509-524.
[18]Babuska R, Verbruggon H B, Vancan H J L. Fuzzy Modeling of Enzymatic penicillin-G Anversion[J]. Engineering Application of Artificial Intelligence,1999,12(1):79-92.
[19]熊智华,王雄,徐用懋.一种利用多神经网络结构建立非线性软测量模型的方法[J].控制与决策,2000,15(2)：173-176.
[20]王旭东,邵惠鹤,罗荣富.分布式RBF神经网络及其在软测量方面的作用[J].控制理论与应用,1998,15(4)：558-563.
[21]王旭东,邵惠鹤.基于神经网络的通用软测量技术[J].自动化学报,1998,24(5)：702-706.
[22]王宏伦,终明安,戴冠中.基于分类／组合的模糊神经元网络[J].信息与控制,1999,28(7)：693-696.
[23]程华农,钱宇,李秀喜,李荷华,江燕斌.化工过程系统集成建模的面向智能体方法[J].化工学报,2003,54(1)：128-130
[24]Cho S Z, Cho Y J, Yoon S C. Reliable Roll Force Prediction in Cold Mill Using Multiple Neural Networks[J]. IEEE Tran. Neural Networks.1997,8(4):874-880.
[25]黄道平,朱学峰,周其节.基丁一种集成模型的多变量非线性预测控制[J].控制理论与应用,1999,16(1)：38-42.
[26]秦秀娟,陈宗海.汽油辛烷值神经网络预测模型的设计[J].控制与决策,1999,14(2)：151-155.
[27]Wang Y, Rong G. A Self-organizing Neural-network-based Fuzzy System[J]. Fuzzy Sets and Systems,1999,103:1-11.
[28]吴建峰,何小荣,陈丙珍.一种用于动态化工过程建模的反馈神经网络新结构[J].化工学报,2002,53(2)：156-160.
[29]Detlef N, Kruse R. Neural-fuzzy Systems for Function Approximation[J]. Fuzzy Sets and Systems,1999,101:261-271.
[30]Grosdidier P, Connor P, Hollifield B, Kulkarni S. A Path forward for DCS Alarm Management[J]. Hydrocarbon Processing,2003, November:59-64.
[31]Brown N. Effective Alarm Management[J]. Hydrocarbon Processing,2004, January: 68-71.
[32]Chao C S, Liu A C. An Alarm Management Framework for Automated Network Fault Identification[J]. Computer Communications,2004,27(13):1341-1353.
[33]J.de Wit. EEMUA Recommendations for the Design and Construction of Refrigerated Liquefied Gas Storage Tanks [J]. Cryogenics,1998,28(12):800-804.
[34]Domijan P, Kalpic D. Off-line Energy Optimization Model for Crude Distillation Unit[J]. Industrial Electronics.2005,1:199-204.
[35]Coca D. Review of Results and Perspectives of Nonlinear Process Identification from Experimental Data[J]. Space Res.,2003,32(3):331-345.
[36]Nakaiwa M., Huang K., Naito K.. Parameter Analysis and Optimization of Ideal Heat Integrated Distillation Columns[J]. Computers and Chemical Engineering,2001,25: 737-744.
[37]Low K.H., Sorensen E.. Simultaneous Optimal Configuration, Design and Operation of Batch Distillation[J]. AICHE Journal,2005,51(6):1700-1713.
[38]Bhaskar V., Gupta S.K., Ray A.K.. Multiobjective Optimization of an Industrial Wiped Film Poly (Ethylene Terephthalate) Reactor:Some further Insights[J]. Computers and Chemical Engineering,2001,25:391-407.
[39]Bhaskar V., Gupta S.K., Ray A.K.. Multiobjective Optimization of an Industrial Wiped-Film Pet Reactor[J]. AICHE Journal,2000,46(5):1046-1058.
[40]Kasat R.B., Kunzru D., Saraf D.N., Gupta S.K.. Multiobjective Optimization of Industrial FCC Units Using Elitist Nondominated Sorting Genetic Algorithm[J]. Ind.Eng.Chem.Res., 2002,41(19),4765-4776.
[41]Rajesh J.K., Gupta S.K., Rangaiah G.P., Ray A.K.. Multi-objective Optimization of Industrial Hydrogen Plants[J]. Chemical Engineering Science,2001,56(3):999-1010.
[42]Cai Wen. Extension theory and its application[J]. Chinese Science Bulletin,1999,44(17): 1538-1548.
[43]Cai Wen, Yang Chunyan, Lin Weichu. Extension Engineering Methods[M]. Beijing: Science Press,2003.
[44]Guowei Yang. Intelligentized and Modeling Conceptual Design Based on the Analysis of Matter Element Dynamic System[J]. Computer Engineering and Applications,2005, 41(16):109-113.
[45]王广鹏,赵燕伟.面向可拓知识集成的创新设计系统研究[J].机电工程,2003,10：132-132.
[46]向阳,于长锐.基于知识的规划模型构造系统研究[J].系统工程学报,2002,17(1)：72-77.
[47]胡宝清.区域水环境质量的区间可拓评价方法及应用[J].中国工程科学,2001,3(6)：53-56.
[48]戴琳.可拓学在工程质量评定中应用的研究[J].南京师范大学学报(工程技术版),2002,2(3)：21-25.
[49]赵燕伟,张国贤.可拓故障诊断方法及其应用[J].机械工程学报,2001,37(9)：39-43.
[50]黄文涛,赵学增,王伟杰.基于物元模型的电力变压器故障的可拓诊断方法[J].电力系统自动化,2004,28(13)：45-49.
[51]王万良,吴刚.分层多变量可拓控制器及其应用[J].广东工业大学学报,1999,16(4)：102-105.
[52]阳林,吴黎明,黄爱华.可拓控制的物元模型及其控制算法[J].系统工程理论与实践,2000,20(6)：126-130.
[53]车录锋,周晓军,徐志农,程耀东.可拓方法在多传感器信息融合工件识别中的应用[J].系统工程理论与实践,2000,8：91-94.
[54]龚京忠,邱静,李国喜,李伟.产品模块可拓变型设计方法[J].计算机集成制造系统,2008,14(7)：1256-1267.
[55]楼健人,伊国栋,张树有,谭建荣.基于知识的产品可拓配置与进化设计技术研究[J].浙江大学学报(工学版),2007,41(3)：466-470.
[56]苏楠,赵燕伟,唐辉军,赵富贵,张峰,桂元坤.基于可拓逻辑的产品族可配置规划研究[J].计算机集成制造系统,2008,14(10)：1897-1903.
[57]周鸣争,杨益民.菱形思维的可拓神经网络实现[J].系统工程理论与实践,2000,6：121-124
[58]王鸿洁,常国岑.可拓神经网络在可拓专家系统中的研究与应用[J].系统L程与电子技术,2005,27(2)：264-266
[59]孙佰清,刑爱国,张积宾,潘启树.可拓神经网络模型的设计与实现[J].哈尔滨工业大学学报,2006,38(7)：1157-1159.
[60]郑鑫,秦建军,陈汉辉,李伟宏.基于可拓学的自然语言处理与系统建模研究[J].哈尔滨工业大学学报,2006,38：1209-1212.
[61]卢荣德,陈宗海,王雷.思维模拟在复杂工业过程建模中应用的综述[J].信息与控制,2002,4(31)：346-352.
[62]蔡文,杨春燕,林伟初.可拓工程方法[M].北京：科学出版社,1997.
[63]杨春燕.事元及其应用[J].系统工程理论与实践,1998,2：80-86.
[64]杨春燕,蔡文.可拓工程研究[J].中国工程科学,2000,2(12)：90-96.
[65]李立希,李嘉.可拓知识库系统及其应用[J].中国工程科学,2001,3(3)：61-64.
[66]蔡文,杨春燕,何斌.可拓逻辑初步[M].北京：科学出版社,2003.
[67]杨春燕,张拥军,蔡文.可拓集合及其应用研究[J].数学实践与认识,2002,32(2)：301-303.
[68]胡宝清.区间上的可拓集及其关联函数[J].广东工业大学学报,2000,17(2)：101-04.
[69]高洁,谢敬东.基于关联函数的变压器故障可拓诊断方法[J].系统工程,2000,18(5)：64-69.
[70]高洁,戴建新,王雪红.可拓决策方法综述[J].系统工程理论方法应用,2004,13(3)：264-271.
[71]李立希,杨春燕,李铧汶.可拓策略生成系统[M].北京：科学出版社,2006.
[72]Mu Shengjing, Su Hongye, Gu Yong, Chu Jian. Multi-objective Optimization of Industrial Purified Terephthalic Acid Oxidation Process[J]. Chinese J. Chem. Eng.,2003,11(5): 536-541.
[73]Dorn, C., Morari, M.. Qualitative Analysis for Homogenous Azeotropic Distillation.1. Local Stability[J]. Ind. Eng. Chem. Res.,2002,41(16):3930-3942.
[74]Weiyang Cheong, Paul I Barton. Azeotropic Distillation in a Middle Vessel Batch Column.3.Model Validation[J]. Ind. Eng.Chem. Res.,1999,38:1549-1564.
[75]Chien, I.L., Wang, C.J., Wong, D.S.H.. Dynamics and Control of a Heterogeneous Azeotropic Distillation Column:Conventional Control Approach[J]. Ind. Eng. Chem. Res.,1999,38:468-478.
[76]Guo, Z., Chin, J., Lee, J.W.. Feasibility of Continuous Reactive Distillation with Azeotropic Mixtures[J]. Ind. Eng. Chem. Res.,2004,43:3758-3769.
[77]Feng, G.Y., Fan, L.T., Seib, P.A., Bertok, B., Kalotai, L., Friedler, F.. Graph-Theoretic Method for the Algorithmic Synthesis of Azeotropic-Distillation System[J]. Ind. Eng. Chem. Res.,2003,42:3602-3611.
[78]Eleonora Bonanomi, Manfred Morari, Phase-Plane Analysis of Homogeneous Azeotropic Distillation Columns[J]. Ind. Eng. Chem. Res.,2002,41:3963-3969.
[79]J.F. Mastral, C. Berrueco, J. Ceamanos. Modeling of the Pyrolysis of High Density Polyethylene Product Distribution in a Fluidized Bed Reactor[J]. J. Anal. Appl. Pyrolysis, 2007,79:313-322.
[80]杨晓梅,华贲,李国庆.低压高密度聚乙烯装置反应系统模型开发[J].计算机与应用化学,2004,21(1)：127-131.
[8l]王淑清.低压高密度聚乙烯装置动态模拟模型开发策略浅谈[J].现代化工,2003,23(3)：44-47.
[82]Yuan XU, Qunxiong ZHU. Extension Theory-based Modeling for Purified Terephthalic Acid Solvent System[A]. The 8th IEEE International Conference on Control & Automation,2010, Xiamen, China.
[83]Yuan XU, Qunxiong ZHU. A New Process Modeling Method Based on Extension Theory and Its Application in Purified Terephthalic Acid Solvent System[A]. The 20th International Conference on Multiple Criteria Decision Making (MCDM2009),2009, 154-157, Chengdu, China.
[84]Ling Wang, Jian Chu, Jun Wu. Selection of Optimum Maintenance Strategies Based on Fuzzy Analytic Hierarchy Process[J]. International Journal of Production Economics, 2007,107(1):151-163.
[85]E.H.Forman, S.I.Gass. The Analytic Hierarchy Process-An Exposition[J]. Operations Research,2001,49(4):469-486.
[86]Athanasios I. Chatzimouratidis, Petros A.Pilavachi. Multicriteria Evaluation of Power Plants Impact on the Living Standard Using the Analytic Hierarchy Process[J]. Energy Policy,2008,36(3):468-478.
[87]Willis.M.J., Di Massimo.C., Montague.G.A., Tham.M.T., Morris.A.J.. Artificial Neural Networks in Process Engineering[J]. IEE Proceedings-D,1991,138(3):256-266.
[88]Wang Weibin, Zheng Pi'e, Li Jinyong. Application of BP NN and RBF NN in Modeling Activated Sludge System [J]. Transaction of Tianjin University.2003,9(3):235-240.
[89]Weixiang Zhao, Dezhao Chen, Shangxu Hu. Detection of Outlier and a Robust BP Algorithm against Outlier[J]. Computers and Chemical Engineering,2004,28:1403-1408.
[90]A.T.C.Goh. Back-propagation Neural Networks for Modeling Complex Systems[J]. Artificial Intelligence in Engineering,1995,9:143-151.
[91]B.H.M.Sadeghi. A BP-neural Network Predictor Model for Plastic Injection Molding Process[J]. Journal of Materials Processing Technology,2000,103(3):411-416.
[92]Specht, D.F.. A General Regression Neural Network[J]. IEEE Transactions on Neural Networks,1991,2 (6):258-276.
[93]Li, Z.W., Sun, J.Z., ZHANG, Z.Q.. Reconstruction of Novel Viewpoint Image Using GRNN[J]. Transactions of Tianjin University,2003,2 (9):136-139.
[94]Mark T.Leung, An-Sing Chen, Hazem Daouk. Forecasting Exchange Rates Using General Regression Neural Networks[J]. Computers and Operations Research,2000,27(11): 1093-1110.
[95]Masters.T, Land.W.. A New Training Algorithm for the General Regression Neural Network[A]. IEEE International Conference on Systems, Man, and Cybernetics,1997,3: 1990-1194.
[96]Yuan XU, Qunxiong ZHU. Research and Implementation of Decreasing the Acetic Acid Consumption in Purified Terephthalic Acid Solvent System[J]. Chinese Journal of Chemical Engineering,2008,16 (4):650-655.
[97]Zhang Jian,Kang Jingli,Wang Minnan. A RBF Network Based Nonlinear Modeling of Diesel Engine[J]. Transaction of CSICE.2003,21(3):221-226.
[98]Ying Tan, Jun Wwang, Jacek M.Zurada. Nonlinear Blind Source Separation Using a Radial Basis Function Network[J]. IEEE Transactions on Neural Networks,2001,12(1): 124-134.
[99]D.L.Yu, J.B.Gomm, D.Williams. Sensor Fault Diagnosis in a Chemical Process via RBF Neural Networks[J]. Control Engineering Practice,1999,7(1):49-55.
[100]Yuan XU, Qunxiong ZHU. A New Method for Monitoring Management in Chemical Process[A]. The 1st International Conference on Information Science and Engineering (ICISE2009),2009, Nanjing, China.
[101]徐圆,朱群雄.基于物元分析的过程工业报警优化[J].化工学报,2008,59(7)：1609-1614.
[102]徐圆,朱群雄.可拓理论在流程工业中的应用[J].控制工程,2008,15(3)：283-286.
[103]Yuan XU, Qunxiong ZHU. A New Design Method for Energy Saving and Consumption Reducing of Process Industry Based on Extension Theory[J]. International Journal of Innovative Computing, Information and Control,2010,6 (5).
[104]Yuan XU, Qunxiong ZHU. Scheme Design for Energy Saving and Consumption Lowing of Process Industry Based on Extension Theory [A]. The 3nd International Symposium on Computational Intelligence and Industrial Applications (ISCIIA 2008),2008,435-443, Dali, China.
[105]徐圆,朱群雄.基于可拓理论的过程工业智能操作优化方法及应用[J].化工学报,2009,60(10)：126-132.