基于CHEMCAD用户接口技术的石化过程虚拟检测系统研究
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摘要
石化企业的自动化生产程度的高低很大程度上影响着我国国民经济,其中准确、及时的过程检测是实现自动化的基本保障。目前,如何利用现代计算机信号处理和过程模拟技术提高过程检测水平,保证生产的安全高效进行,降低成本以获得更高的经济效益,已经成为一个重要课题。
本文分析了现有的过程检测的执行方式,针对石化过程检测中迫切需要实现的现代滤波技术保证的数字滤波技术、实时在线检测和对检测难度很大的检测变量的软测量,提出使用基于CHEMCAD用户接口技术的过程虚拟检测的方法,利用CHEMCAD在化工过程模拟计算上的优势,结合现代滤波技术,建立以COM技术为手段、以现代数字滤波为保障,以过程模拟计算为核心,以石化过程检测为研究对象的虚拟检测模式;通过EXCEL程序将各个模块组件有机结合,对过程检测数据进行显示、分析、统计,实现测、图、表、管一体化。并可与现有石化过程检测系统整合,如:DCS系统,实现过程的实时检测、预估,并为过程的在线优化和先进控制提供了技术条件。
为了实现基于CHEMCAD用户接口技术的过程虚拟检测系统,作者进行了有益的尝试。在EXCEL程序中,使用VBA语言和Microsoft COM组件技术,针对实际丙烯精馏单元完成了该系统的实例程序,证明了其可行性,并对各种集成手段和程序功能进行了讨论和实现。
Petrochemical enterprise is so important for the economy of our country that its degree of automation, which depends on the exact and opportune process detection, directly affects the national economy total value. Currently, it is in a low level in the world, so how to improve the process detection by modern computer signal processing and process simulation, for the purpose of production safe and efficiency, reducing the costs and getting better economical benefit, has become a critical task that needs to be solved immediately.
With the analysis of the current process detection, a new pattern of process virtual detection system based on the CHEMCAD user interface has been developed, given that the digital filtering, online detection and soft-measurement are cried for in petrochemical process. By taking the advantage of CHEMCAD in chemical process simulation and integrating with the modern signal filtering, the virtual detection mode, which depends on the COM interface, modern digital filtering and process simulation, is described. The new pattern should integrate every module and realize the integration of detection, graphs, tables and operation, also with the petrochemical process detection system in existence, such as the DCS. By real time detection and prediction, the new application makes the online optimization and advanced control come true.
In order to realize the virtual detection system in petrochemical process based on CHEMCAD user interface, the author has designed the application with VBA language and Microsoft COM interface in EXCEL, which based on the propylene distillation unit. It has proved the correctness and the feasibility of the new pattern and its program code.
本文分析了现有的过程检测的执行方式,针对石化过程检测中迫切需要实现的现代滤波技术保证的数字滤波技术、实时在线检测和对检测难度很大的检测变量的软测量,提出使用基于CHEMCAD用户接口技术的过程虚拟检测的方法,利用CHEMCAD在化工过程模拟计算上的优势,结合现代滤波技术,建立以COM技术为手段、以现代数字滤波为保障,以过程模拟计算为核心,以石化过程检测为研究对象的虚拟检测模式;通过EXCEL程序将各个模块组件有机结合,对过程检测数据进行显示、分析、统计,实现测、图、表、管一体化。并可与现有石化过程检测系统整合,如:DCS系统,实现过程的实时检测、预估,并为过程的在线优化和先进控制提供了技术条件。
为了实现基于CHEMCAD用户接口技术的过程虚拟检测系统,作者进行了有益的尝试。在EXCEL程序中,使用VBA语言和Microsoft COM组件技术,针对实际丙烯精馏单元完成了该系统的实例程序,证明了其可行性,并对各种集成手段和程序功能进行了讨论和实现。
Petrochemical enterprise is so important for the economy of our country that its degree of automation, which depends on the exact and opportune process detection, directly affects the national economy total value. Currently, it is in a low level in the world, so how to improve the process detection by modern computer signal processing and process simulation, for the purpose of production safe and efficiency, reducing the costs and getting better economical benefit, has become a critical task that needs to be solved immediately.
With the analysis of the current process detection, a new pattern of process virtual detection system based on the CHEMCAD user interface has been developed, given that the digital filtering, online detection and soft-measurement are cried for in petrochemical process. By taking the advantage of CHEMCAD in chemical process simulation and integrating with the modern signal filtering, the virtual detection mode, which depends on the COM interface, modern digital filtering and process simulation, is described. The new pattern should integrate every module and realize the integration of detection, graphs, tables and operation, also with the petrochemical process detection system in existence, such as the DCS. By real time detection and prediction, the new application makes the online optimization and advanced control come true.
In order to realize the virtual detection system in petrochemical process based on CHEMCAD user interface, the author has designed the application with VBA language and Microsoft COM interface in EXCEL, which based on the propylene distillation unit. It has proved the correctness and the feasibility of the new pattern and its program code.
引文
[1]Benneff P. Virtual instrument. Electronic Products, 1993, 15(7):37~39
[2]刘建成,蒋新华,吴今培,一种机电设备状态虚拟检测系统的实现,信息与控制,2003,32(6):564~567
[3]王泉,制动器虚拟检测系统及其检测方法的研究:[硕士学位论文],北京;北京工商大学,2002
[4]袁永根,李华生,过程系统测量数据校正技术,北京:中国石化出版社,1996
[5]Kuehn D.R., Davidson H., Computer control II. Mathematics of control. Chem. Eng. Pro., 1961, 57(6):44~47
[6]Brit H.I.,R. H. Leucke, The estimation of parameters in nonlinear implicit models,Technometrics,1973,15(2):233~247
[7]Vaclavek V., Loucka M, Calculation of material balance for chemical engineering systems with due allowance for measurement errors Chem. Eng. Sci., 1976, 31:1199-1205
[8]Knepper J.C, Gorman J.W. Statistical analysis of constrained data sets. AICHE J.1989, 35(5):869
[9]Beckman J.R. Data adjustment for non-reactive batch or steady state processes.Chem.Eng.commun.1982, 15:357
[10]Crowe C.M. Reconciliation of process flow rates by matrix projection, Part II: the nonlinear case. AICHE J.1988, 32(4):616~623
[11]David R.H. Diagnostic reasoning based on structure and behavior. Al. 1984,24
[12].Romagnoli J.A. On data reconciliation: constraints processing and treatment of bias. Chem.Eng.Sci.1983, 44(7):553
[13]In-Won Kim et al. Robust error in variables estimation using nonlinear programming techniques. AICHE J.1990, 36:985~996
[14]Tjoa L.B, L.T.Biegler. Simultaneous strategies for data reconciliation and gross error detection of nonlinear systems. Computers and Chemical Engineering. 1991, 15(10):679~690
[15]Johnstom L.P.M, M.A.Kramer. Maximum likelihood data rectification: steady-state systems. AICHE J.1995, 41(11):2415~2426
[16] 刘 传 政 , 袁 一 , 关 于 化 工 数 据 校 正 问 题 研 究 , 化 学 工 程 ,1994,22(6):69~72
[17]李红军,秦永胜等,化工过程中的数据协调及显著误差的检验,化工自动化及仪表,1997,24(2):25~32
[18]Gorczynski E.W. Making the most of your plant data. PSE85, Inst of Chem.Eng.Symp.Ser.1985, 92:251
[19]Bossen B.S, L.J.Christiansen, J.E.Jarvan, et al. Simulation, optimization and data-reconciliation of industrial chemical processes. Chemical engineering research&design, Part A: Transactions of the institute of chemical engineers. 1994, 72(A3)376~381
[20]Albers J.E. Data reconciliation with unmeasured variables. Hydrocarbon Process. 1994, 73(3):65~66
[21]Moo Ho Lee et al. Hierarchical on-line data reconciliation and optimization for an industrial utility plant. Comp.Chem.Eng.1998, 22, suppl: 247
[22]J.D.Kelly, M.Darouach. Fault-detection of multiple biases or process leaks in linear steady state system. Computers and Chemical Engineering. 1999, 22(12):1771
[23]周传光,基于过程模拟与神经网络的测量数据在线校正技术集成化研究:[博士学位论文],广州;华南理工大学,1999
[24]Darouach Mohamed, Michel Zasadzinski. Data reconciliation in generalized linear dynamic systems. AICHE J.1991, 37(2):193~201
[25]Liebman M.J, TF.Edgar, L.S.Lasdon. Efficient data reconciliation and estimation for dynamic processes using nonlinear programming techniques. Comp & Chem Eng.1992, 16(10):963~986
[26]Albuquerque J.S, L.T.Biegler. Decomposition algorithms for on-line estimation with nonlinear model. Comp & Chem Eng.1995, 19(10):1031~1039
[27]Karen F. Mcbrayer et al. The application of nonlinear dynamic data reconciliation to plant data Comp & Chem Eng.1998, 22(12):1907
[28]沈福民,自适应信号处理,西安:西安电子科技大学出版社,2001
[29]S M Ross. Stochastic Process. John Wily & Sons, 1983
[30]G E P Box, G M Jenkins, G C Reinsel. Time Series Analysis: Forecasting and Control. Prentice-Hall, 1994
[31]Alexander , S. T. Adaptive Signal Processing : Theory and Applications. Springer-Verlag, 1986
[32]M B Prestley. Spectral Analysis and Time Series. Academic Press,1981
[33]Chemstations Inc., CHEMCAD User Guide and Tutorial, 2003
[34]天津拓普计算机工程有限公司,在线实时过程模拟监测和优化,2002
[35]陈冬怀,高景昌,杨亚红,COM 的自动化技术的研究与应用,吉林大学学报:信息科学版,2004, 22(2):138~142
[36]冯少荣,DCOM/CORBA 技术的研究及应用,信息与电子工程,2004, 2(2):143~146
[37]江永健,郭学俊,基于 MTS/COM 的多层分布式系统应用,微型机与应用,2003, 22(11):26~29
[38]李晓玫,杨小平,Excel 中的 VBA 程序设计,四川师范大学学报:自然科学版,2004, 27(4):423~426
[39]MathWorks Inc., MATLAB Application Program Interface Guide, 1998
[40]夏和青,利用 Aspen plus 模拟软件挖潜丙烯精馏塔,炼油技术与工程,2003,7,44~46
[41]MOHAMED A H,SCHWARZ K P. Adaptive Kalman Filtering for INS/GPS. Journal of Geodesy, 1999, 73(4):193~203
[42]王耀南,计算机智能信息处理技术,长沙:湖南大学出版社,1998
[43]刘树棠,信号与系统,西安:西安交通大学出版社,1999
[44]赵茂泰,智能仪器原理及应用,北京:电子工业出版社,1999
[45]钱学森,宋健,工程控制论 (下册),北京:科学出版社,1981
[46]Brown. R. G. , P. Y. C. Hwang. Introduction to Random Signals and Applied Kalman Filtering, Second Edition. John Wiley & Sons, Inc. 1992
[47]陆光华,彭学愚,随机信号处理,西安:西安电子科技大学出版社,2002,76~78
[48]Wickrhauser M V. Adapted wavelet analysis from theory to sofeware. Wellesley-Mass Press, 1994
[49]应怀樵,虚拟仪器与计算机采集测试分析仪器的发展和展望,测控技术,2000,19(8):4~6
[50]欧阳黎明,MATLAB 控制系统设计,北京:国防工业出版社,2001
[51]程桂明等,应用 MATLAB 语言处理数字信号与数字图像,北京:科学出版社,2000
[52]庄芹仙,流程模拟技术在石油化工中的应用,化学工程,1997,25(1):59~62
[53]Chemstations Inc., EXCEL UNIT User Manual, 2003
[54]Chemstations Inc., CHEMCAD 5 SERVICES TO VISUAL BASIC APPLICATIONS, 2003
[55]Chemstations Inc., CHEMCAD 5 Help, 2003
[2]刘建成,蒋新华,吴今培,一种机电设备状态虚拟检测系统的实现,信息与控制,2003,32(6):564~567
[3]王泉,制动器虚拟检测系统及其检测方法的研究:[硕士学位论文],北京;北京工商大学,2002
[4]袁永根,李华生,过程系统测量数据校正技术,北京:中国石化出版社,1996
[5]Kuehn D.R., Davidson H., Computer control II. Mathematics of control. Chem. Eng. Pro., 1961, 57(6):44~47
[6]Brit H.I.,R. H. Leucke, The estimation of parameters in nonlinear implicit models,Technometrics,1973,15(2):233~247
[7]Vaclavek V., Loucka M, Calculation of material balance for chemical engineering systems with due allowance for measurement errors Chem. Eng. Sci., 1976, 31:1199-1205
[8]Knepper J.C, Gorman J.W. Statistical analysis of constrained data sets. AICHE J.1989, 35(5):869
[9]Beckman J.R. Data adjustment for non-reactive batch or steady state processes.Chem.Eng.commun.1982, 15:357
[10]Crowe C.M. Reconciliation of process flow rates by matrix projection, Part II: the nonlinear case. AICHE J.1988, 32(4):616~623
[11]David R.H. Diagnostic reasoning based on structure and behavior. Al. 1984,24
[12].Romagnoli J.A. On data reconciliation: constraints processing and treatment of bias. Chem.Eng.Sci.1983, 44(7):553
[13]In-Won Kim et al. Robust error in variables estimation using nonlinear programming techniques. AICHE J.1990, 36:985~996
[14]Tjoa L.B, L.T.Biegler. Simultaneous strategies for data reconciliation and gross error detection of nonlinear systems. Computers and Chemical Engineering. 1991, 15(10):679~690
[15]Johnstom L.P.M, M.A.Kramer. Maximum likelihood data rectification: steady-state systems. AICHE J.1995, 41(11):2415~2426
[16] 刘 传 政 , 袁 一 , 关 于 化 工 数 据 校 正 问 题 研 究 , 化 学 工 程 ,1994,22(6):69~72
[17]李红军,秦永胜等,化工过程中的数据协调及显著误差的检验,化工自动化及仪表,1997,24(2):25~32
[18]Gorczynski E.W. Making the most of your plant data. PSE85, Inst of Chem.Eng.Symp.Ser.1985, 92:251
[19]Bossen B.S, L.J.Christiansen, J.E.Jarvan, et al. Simulation, optimization and data-reconciliation of industrial chemical processes. Chemical engineering research&design, Part A: Transactions of the institute of chemical engineers. 1994, 72(A3)376~381
[20]Albers J.E. Data reconciliation with unmeasured variables. Hydrocarbon Process. 1994, 73(3):65~66
[21]Moo Ho Lee et al. Hierarchical on-line data reconciliation and optimization for an industrial utility plant. Comp.Chem.Eng.1998, 22, suppl: 247
[22]J.D.Kelly, M.Darouach. Fault-detection of multiple biases or process leaks in linear steady state system. Computers and Chemical Engineering. 1999, 22(12):1771
[23]周传光,基于过程模拟与神经网络的测量数据在线校正技术集成化研究:[博士学位论文],广州;华南理工大学,1999
[24]Darouach Mohamed, Michel Zasadzinski. Data reconciliation in generalized linear dynamic systems. AICHE J.1991, 37(2):193~201
[25]Liebman M.J, TF.Edgar, L.S.Lasdon. Efficient data reconciliation and estimation for dynamic processes using nonlinear programming techniques. Comp & Chem Eng.1992, 16(10):963~986
[26]Albuquerque J.S, L.T.Biegler. Decomposition algorithms for on-line estimation with nonlinear model. Comp & Chem Eng.1995, 19(10):1031~1039
[27]Karen F. Mcbrayer et al. The application of nonlinear dynamic data reconciliation to plant data Comp & Chem Eng.1998, 22(12):1907
[28]沈福民,自适应信号处理,西安:西安电子科技大学出版社,2001
[29]S M Ross. Stochastic Process. John Wily & Sons, 1983
[30]G E P Box, G M Jenkins, G C Reinsel. Time Series Analysis: Forecasting and Control. Prentice-Hall, 1994
[31]Alexander , S. T. Adaptive Signal Processing : Theory and Applications. Springer-Verlag, 1986
[32]M B Prestley. Spectral Analysis and Time Series. Academic Press,1981
[33]Chemstations Inc., CHEMCAD User Guide and Tutorial, 2003
[34]天津拓普计算机工程有限公司,在线实时过程模拟监测和优化,2002
[35]陈冬怀,高景昌,杨亚红,COM 的自动化技术的研究与应用,吉林大学学报:信息科学版,2004, 22(2):138~142
[36]冯少荣,DCOM/CORBA 技术的研究及应用,信息与电子工程,2004, 2(2):143~146
[37]江永健,郭学俊,基于 MTS/COM 的多层分布式系统应用,微型机与应用,2003, 22(11):26~29
[38]李晓玫,杨小平,Excel 中的 VBA 程序设计,四川师范大学学报:自然科学版,2004, 27(4):423~426
[39]MathWorks Inc., MATLAB Application Program Interface Guide, 1998
[40]夏和青,利用 Aspen plus 模拟软件挖潜丙烯精馏塔,炼油技术与工程,2003,7,44~46
[41]MOHAMED A H,SCHWARZ K P. Adaptive Kalman Filtering for INS/GPS. Journal of Geodesy, 1999, 73(4):193~203
[42]王耀南,计算机智能信息处理技术,长沙:湖南大学出版社,1998
[43]刘树棠,信号与系统,西安:西安交通大学出版社,1999
[44]赵茂泰,智能仪器原理及应用,北京:电子工业出版社,1999
[45]钱学森,宋健,工程控制论 (下册),北京:科学出版社,1981
[46]Brown. R. G. , P. Y. C. Hwang. Introduction to Random Signals and Applied Kalman Filtering, Second Edition. John Wiley & Sons, Inc. 1992
[47]陆光华,彭学愚,随机信号处理,西安:西安电子科技大学出版社,2002,76~78
[48]Wickrhauser M V. Adapted wavelet analysis from theory to sofeware. Wellesley-Mass Press, 1994
[49]应怀樵,虚拟仪器与计算机采集测试分析仪器的发展和展望,测控技术,2000,19(8):4~6
[50]欧阳黎明,MATLAB 控制系统设计,北京:国防工业出版社,2001
[51]程桂明等,应用 MATLAB 语言处理数字信号与数字图像,北京:科学出版社,2000
[52]庄芹仙,流程模拟技术在石油化工中的应用,化学工程,1997,25(1):59~62
[53]Chemstations Inc., EXCEL UNIT User Manual, 2003
[54]Chemstations Inc., CHEMCAD 5 SERVICES TO VISUAL BASIC APPLICATIONS, 2003
[55]Chemstations Inc., CHEMCAD 5 Help, 2003