全部 标题 作者
关键词 摘要

OALib Journal期刊
ISSN: 2333-9721
费用:99美元

查看量下载量

相关文章

更多...
化工学报  2013 

化工过程软测量建模方法研究进展

DOI: 10.3969/j.issn.0438-1157.2013.03.003, PP. 788-800

Keywords: 软测量,建模,辨识,非线性建模,数据驱动建模,非线性动态建模

Full-Text   Cite this paper   Add to My Lib

Abstract:

软测量仪表是解决化工过程中质量变量难以实时测量的重要手段。软测量仪表的核心问题是软测量建模。阐述了软测量建模与辨识和非线性建模的关系:质量变量和易测变量的动态关系存在于增量之间,辨识模型依赖于增量数据,软测量建模则是依赖于实测变量数据来获取这个动态关系;非线性建模建立了变量间的静态关系,忽略了对象动态特性,而软测量建模要兼顾对动态特性的表征。随着人们对过程特性的认识加深,软测量建模方法不断发展,经历了从机理建模到数据驱动建模,从线性建模到非线性建模,从静态建模到动态建模的过程。详细讨论了软测量建模的发展过程,众多建模方法的优缺点及适用情况和现在建模的热点,最后对软测量建模方法进行了总体展望。

References

[1]  Li W,Yue H H,Valle C S,et al.Recursive PCA for adaptive process monitoring[J].Journal of Process Control,2000,10(5):471-486
[2]  Qin S J,McAvoy T J.Nonlinear PLS modeling using neural networks[J].Computers & Chemical Engineering,1992,16(4):379-391 target="_blank">
[3]  Principe J C,Euliano N R,Lefebvre W C.Neural and Adaptive Systems [M].New York:Wiley,2000:197-210
[4]  Qin S J.Neural Networks for Intelligent Sensors and Control-Practical Issues and Some Solutions [M].New York:Academic Press,1996:213-234
[5]  Theodoros E,Tomaso P,Massimiliano P.Regularization and statistical learning theory for data analysis[J].Computational Statistics and Data Analysis,2002,38(4):421-432
[6]  Chen X,Gao F R,Chen G H.A soft-sensor development for melt-flow-length measurement during injection mold filling[J].Materials Science and Engineering A,2004,384(1):245-254
[7]  Wang Xudong(王旭东),Shao Huihe(邵惠鹤),Luo Rongfu(罗荣富).The distributed RBF neural network and its application in soft sensor[J].Control Theory & Applications(控制理论与应用),1998,15(4):558-563 Theory --- unreasonable DOI found: doi=Control Theory target="_blank">
[8]  Angelov P,Buswell R.Identification of evolving fuzzy rule-based models[J].IEEE Transactions on Fuzzy Systems,2002,10(5):667-677
[9]  Arazo M J,Cano J M,Gmez S E,et al.Automatization of a penicillin production process with soft sensors and an adaptive controller based on neuro fuzzy systems[J].Control Engineering Practice,2004,12(9):1073-1090
[10]  Wang Y H,Huang D X,Gao D J,et al.Wavelet networks based soft sensor and predictive control in fermentation process[J].Computer Aided Chemical Engineering,2003,15(6):1222-1227
[11]  Jimenez A, Beltran G, Aguilera M P, et al. A sensor-software based on artificial neural network for the optimization of olive oil elaboration process[J].Sensors and Actuators:B. Chemical,2008, 129(2):985-990
[12]  Liu Ruilan(刘瑞兰).Some studies on soft sensor technology and their applications to industry process.Hangzhou:Zhejiang University,2004
[13]  Rong H J,Sundararajan N,Huang G B,et al.Sequential adaptive fuzzy inference system for nonlinear system identification and prediction[J].Fuzzy Sets and Systems,2006,157(9):1260-1275
[14]  Liu Ruilan(刘瑞兰),Su Hongye(苏宏业),Mu Shengjing(牟盛静),et al.Fuzzy neural network model of 4-CBA concentration for industrial purified terephthalic acid oxidation process[J].Journal of Chemical Industry and Engineering(China)(化工学报),2004,12(2):234-239
[15]  Runkler T A,Gerstorfer E,Schlang M,et al.Modeling and optimization of a refining process for fiber board production[J].Control Engineering Practice,2003,11(11):1229-1241
[16]  Jang J S R,Sun C T,Mizutani E.Neuro-Fuzzy and Soft Computing [M].Upper Saddle River,NJ:Prentice Hall,1997:312-345
[17]  Lin F J,Wai R J,Lin C H,et al.Decoupled stator-flux-oriented induction motor drive with fuzzy neural network uncertainty observer[J].IEEE Transactions on Industrial Electronics,2000,47(2):356-367
[18]  Fukuda T,Kubota N.An intelligent robotic system based on a fuzzy approach[J].Proceedings of the IEEE,1999,87(9):1448-1470
[19]  Li Xiuliang(李修亮).Study on soft sensor modeling methods and applications.Hangzhou:Zhejiang University,2009
[20]  Vapnik V.Statistical Learning Theory [M].New York:Wiley,1998:34-56
[21]  Vapnik V.The Nature of Statistical Learning Theory[M].New York:Springer-Verlag,1999:128-194
[22]  Ankti B G,Jyeshtharaj B J,Valadi K J,et al. Development of support vector regression-based correlation for prediction of overall gas hold-up in bubble column reactors for various gas-liquid systems[J].Chemical Engineering Science,2007,62(24):7078-7089
[23]  Yuan P,Mao Z Z,Wang F L.Endpoint prediction of EAF based on multiple support vector machines[J].Journal of Iron and Steel Research,2007,14(2):20-24
[24]  Lin F J,Wai R J,Lin C H,et al.Decoupled stator-flux-oriented induction motor drive with fuzzy neural network uncertainty observer[J].IEEE Transactions on Industrial Electronics,2000,47(2):356-367
[25]  Yan W,Shao H,Wang X.Soft sensing modeling based on support vector machine and Bayesian model selection[J].Computers & Chemical Engineering,2004,28(8):1489-1498 --- unreasonable DOI found: doi=Computers target="_blank">
[26]  Fernando D S,Adriana N A.Biomass estimation in batch biotechnological processes by Bayesian Gaussian process regression[J].Computers & Chemical Engineering,2008,32(12):3264-3273 target="_blank">
[27]  Alexandra G,Jus K,Tor A J.Explicit stochastic predictive control of combustion plants based on Gaussian process models[J].Automatica,2008,44(6):1621-1631
[28]  Kocijan J,Likar B.Gas-liquid separator modeling and simulation with Gaussian-process models[J].Simulation Modelling Practice and Theory,2008,16(8):910-922
[29]  Rainer P.Multiple-step-ahead prediction in control systems with Gaussian process models and TS-fuzzy models[J].Engineering Applications of Artificial Intelligence,2007,20(8):1023-1035
[30]  Bojan L,Jus K.Predictive control of a gas-liquid separation plant based on a Gaussian process model[J].Computers & Chemical Engineering,2007,31(3):142-152 --- unreasonable DOI found: doi=Computers target="_blank">
[31]  Li Xiuliang(李修亮),Su Hongye(苏宏业),Chu Jian(褚健).Multiple model soft sensor based on affinity propagation,Gaussian process and Bayesian committee machine[J].CIESC Journal(化工学报),2009,17(1):95-99
[32]  Fu Yongfeng(傅永峰),Su Hongye(苏宏业),Zhang Ying(张英),et al.Adaptive soft-sensor modeling algorithm based on FCMISVM and its application in PX adsorption separation process[J].Journal of Chemical Industry and Engineering(China)(化工学报),2008,59(5):746-751
[33]  Babak R.A cluster validity index for fuzzy clustering[J].Fuzzy Sets and Systems,2010,161(6):3014-3025
[34]  Qi H Y,Zhou X G,Liu L H,et al.A hybrid neural network-first principles model for fixed-bed reactor[J].Chemical Engineering Science,1999,54(14):2512-2526
[35]  Li Xiangyang(李向阳),Zhu Xuefeng(朱学峰),Liu Huanbin(刘焕彬).Research on hybrid modeling method in batch cooking process[J].Transactions of China Pulp and Paper(中国造纸学报),2001,16(2):24-28
[36]  Prasad V,Schley M,Russo L P,et al.Product property and production rate control of styrene polymerization[J].Journal of Process Control,2002,12(3):353-372
[37]  Fu Y F.Dynamic soft-sensing modeling method and its application in industrial process[J].Process of Automation Instrumentation,2011,32(9):67-70
[38]  Lin Y H,George A C.A new approach to fuzzy-neural system modeling[J].IEEE Transactions on Fuzzy System,1995,3(2):190-198
[39]  Elman J L.Finding structure in time[J].Cognitive Science,1990,14(2):179-211
[40]  Daniel O,Perez C J R,Eduardo A,et al.Soft-sensor for on-line estimation of ethanol concentrations in wine stills[J].Journal of Food Engineering,2008,87(4):571-577
[41]  Shakil M,Elshafei M,Habib M A,et al.Soft sensor for NOx and O2 using dynamic neural networks[J].Computers and Electrical Engineering,2009,35(4):578-586
[42]  Dai X Z,Wang W C,Ding Y H,et al.Assumed inherent sensor inversion based ANN dynamic soft-sensing method and its application in erythromycin fermentation process[J].Computers & Chemical Engineering, 2006,30(8):1203-1225 target="_blank">
[43]  Hong B S,Fan L T,John R S.Monitoring the process of curing of epoxy/graphite fiber composites with a recurrent neural network as a soft sensor[J].Artificial Intelligence,1998,11(2):293-306
[44]  Li C,Wang S L,Zhang X M.Dynamic soft sensor modeling based on multiple least squares support vector machines//Max Q H M.Proceedings of the 7th World Congress on Intelligent Control and Automation. Piscataway,NJ:IEEE Press,2008:25-27
[45]  Luo Jianxu(罗健旭),Shao Huihe(邵惠鹤).Developing dynamic soft sensors using multiple neural networks[J].Journal of Chemical Industry and Engineering(China)(化工学报),2003,54(12):1770-1773
[46]  Li Chuan(李川),Wang Shilong(王时龙),Zhang Xianming(张贤明).Dynamic soft sensor modeling based on multiple relevance vector machines[J].Journal of System Simulation(系统仿真学报),2009,21(12):3513-3517
[47]  Du W L,Guan Z Q,Qian F.The time series soft-sensor modeling based on Adaboost_LS-SVM// Max Q H M. Proceedings of the 8th World Congress on Intelligent Control and Automation.Piscataway,NJ:IEEE Press,2010:1491-1495
[48]  Pedro J L,Alfredo D,Osvaldo A.High-level canonical piecewise linear representation using a simplicial partition[J].IEEE Transactions on Circuits and Systems-I:Fundamental Theory and Applications,1999,46(4):463-480
[49]  Elom D,Huang B,Xu F W,et al.A decoupled multiple model approach for soft sensors design[J].Control Engineering Practice,2011,19(2):126-134
[50]  Li X L,Su H Y,Chu J.Multiple model soft sensor development with irregular/missing process output measurement[J].Control Engineering Practice,2009,17(1):95-99
[51]  Hiromasa K,Kimito F.A soft sensor method based on values predicted from multiple intervals of time difference for improvement and estimation of prediction accuracy[J].Chemometrics and Intelligent Laboratory Systems,2011,109(2):197-206
[52]  Hiromasa K,Kimito F.Maintenance-free soft sensor models with time difference of process variables[J].Chemometrics and Intelligent Laboratory Systems,2011,107(2):312-317
[53]  Bao L,Bodil R,Torben M S,et al.Data-driven soft sensor design with multiple-rate sampled data:a comparative study[J].Industrial & Engineering Chemistry Research,2009,48(5):5379-5387 target="_blank">
[54]  Jochen O,Mihiar A,Matthias K.Identification of a high efficiency boiler based on neural networks with locally distributed dynamics// Misener J.Proceedings of the 1996 IEEE International Symposium on Intelligent Control Dearborn.Piscataway,NJ:IEEE Press,1996:15-18
[55]  Dong D,McAvoy T J.Nonlinear principal component analysis-based on principal curves and neural networks[J].Computers & Chemical Engineering,1996,20(1):65-78 --- unreasonable DOI found: doi=Computers target="_blank">
[56]  Bang Y H,Yoo C K,Lee I B.Nonlinear PLS modeling with fuzzy inference system[J].Chemometrics and Intelligent Laboratory Systems,2003,64(2):137-155
[57]  Facco P,Doplicher F,Bezzo F,et al.Moving average PLS soft sensor for online product quality estimation in an industrial batch polymerization process[J].Journal of Process Control,2009, 19(3):520-529
[58]  Bro R.Multilinear PLS[J].Journal of Chemometrics,1996,10(1):47-61 3.0.CO;2-C target="_blank">
[59]  Shang L F,Lü J C,Yi Z.Rigid medical image registration using PCA neural network[J].Neurocomputing,2006,69(14):1717-1722
[60]  Suykens J A K,Vandewalle J.Least squares support vector machines classifiers[J].Neural Network Letters,1999,9(3):293-300
[61]  Theodoros E,Tomaso P,Massimiliano P.Regularization and statistical learning theory for data analysis[J].Computational Statistics and Data Analysis,2002,38(4):421-432
[62]  Huang C L,Wang C J.A GA-based feature selection and parameters optimization for support vector machines[J].Expert Systems with Applications,2006,31(2):231-240
[63]  Cherkassky V,Ma Y.Practical selection of SVM parameters and noise estimation for SVM regression[J].Neural Networks,2004,17(1):113-126
[64]  Yuan X F,Wang Y N.Parameter selection of support vector machine for function approximation based on chaos optimization[J].Journal of Systems Engineering and Electronics,2008,19(1):191-197
[65]  Kadlec P,Gabrys B,Strandt S.Data-driven soft sensors in the process industry[J].Computers & Chemical Engineering,2009,33(4):795-814 target="_blank">
[66]  Zhong Wei(仲蔚),Yu Jinshou(俞金寿).MIMO soft sensors for hydrocracking fractionators via fuzzy artmap[J].Journal of Chemical Industry and Engineering(China)(化工学报),2000,51(5):671-675
[67]  Kadlec P,Gabrys B,Strandt S.Data-driven soft sensors in the process industry[J].Computers & Chemical Engineering,2009,33(4):795-814 --- unreasonable DOI found: doi=Computers target="_blank">
[68]  Ma Yong(马勇),Huang Dexian(黄德先),Jin Yihui(金以慧).Discuss about dynamic soft-sensing modeling[J].Journal of Chemical Industry and Engineering(China)(化工学报),2005,56(8):1516-1519
[69]  Dae S L,Min W L,Seung H W,et al.Nonlinear dynamic partial least squares modeling of a full-scale biological wastewater treatment plant[J].Process Biochemistry,2006,41(5):2050-2057
[70]  Hui P,Tohru O,Yukihiro T,et al.RBF-ARX model-based nonlinear system modeling and predictive control with application to a NOx decomposition process[J].Control Engineering Practice,2004,12(1):191-203
[71]  David M H.Accounts of experiences in the application of artificial neural networks in chemical engineering[J].Industrial & Engineering Chemistry Research,2008,47(16):5782-5796 target="_blank">
[72]  Tian H P,David S H W,Jang S S.Development of a novel soft sensor using a local model network with an adaptive subtractive clustering approach[J].Industrial & Engineering Chemistry Research,2010,49(10):4738-4747 --- unreasonable DOI found: doi=Industrial target="_blank">
[73]  Zhang D Y,Cao J,Sun L P.Soft sensor modeling of moisture content in drying process based on LSSVM// Cui J P,Qi J M.Proceedings of the 9th International Conference on Electronic Measurement & Instruments .Beijing,China:Institute of Electrical and Electronics,2009:989-993
[74]  Suykens J A K,van G T,De M B.Least Squares Support Vector Machines [M].Singapore:World Scientific,2002:125-142
[75]  Hector J G,Heb Q P,Wang J.A reduced order soft sensor approach and its application to a continuous digester[J].Journal of Process Control,2011,21(4):489-500
[76]  Rangaiah G P,Krishnaswamy P R.Estimating second-order plus dead time model parameters[J].Industrial & Engineering Chemistry Research,1994,33(7):1867-1871 target="_blank">
[77]  Rangaiah G P,Krishnaswamy P R.Estimating second-order dead time parameters from under damped process transients[J].Chemical Engineering Science,1996,51(7):1149-1155
[78]  Fujiwara K,Kano M,Hasebe S,et al.Soft-sensor development using correlation-based just-in-time modeling[J].AIChE Journal,2009,55(7):1754-1765
[79]  Ku W,Storer R,Georgakis C.Disturbance detection and isolation by dynamic principal component analysis[J].Chemometrics and Intelligent Laboratory Systems,1995,30(1):179-196
[80]  Russell E,Chiang L,Braatz R.Fault detection in industrial processes using canonical variate analysis and dynamic principal component analysis[J].Chemometrics and Intelligent Laboratory Systems,2000,51(8):81-93
[81]  Larimore W.Statistical Methods in Control and Signal Processing [M].New York :Marcel Dekker,1997:234-256
[82]  Wu Yao(吴瑶),Luo Xiongling(罗雄麟),Yuan Zhihong(袁志宏).Soft sensor modeling with dynamic interpolation neural network for multirate system[J].Chemical Industry and Engineering Progress(化工进展),2009,28(8):1323-1327
[83]  Daniel S,Pedro A,Pablo E,et al.Adaptive soft-sensors for on-line particle size estimation in wet grinding circuits[J].Control Engineering Practice,2008,16(2):171-178
[84]  Lu W X,Yang Q,Huang D X,et al.A dynamic soft-sensing method based on impulses response template and parameter estimation with modified DE optimization//George S A.Proceedings of the 17th International Federation of Automatic Control Congress.Laxenburg,Austria:IFAC Papers Online,2008:10983-10988
[85]  Du Wenli(杜文莉),Guan Zhenqiang(官振强),Qian Feng(钱锋).Dynamic soft sensor modeling based on time series error compensation[J].CIESC Journal(化工学报),2010,61(2):439-443
[86]  Joseph B,Brosilow C.Inferential control of processes(Ⅰ):Steady state analysis and design[J].AIChE Journal,1978,24(3):485-492
[87]  Brosilow C,Tong M.Inferential control of processes(Ⅱ):The structure and dynamics of inferential control systems[J].AIChE Journal,1978,24(3):492-500
[88]  Joseph B,Brosilow C.Inferential control of processes(Ⅲ):Construction of optimal and suboptimal dynamic estimators[J].AIChE Journal,1978,24(2):500-509
[89]  McAvoy T J.Computational intelligence and soft computing for space applications[J].IEEE Aerospace and Electronic Systems Magazine,1996,11(8):8-10
[90]  Eykhoff P.System Identification—Parameter and State Estimation [M].New York:John Wiley & Sons,1974:10-12
[91]  Strejc V.Least squares parameter estimation[J].Automatica,1980,16(5):535-550
[92]  Sarkar P,Gupta S K.Steady state simulation of continuous-flow stirred-tank slurry propylene polymerization reactors[J].Polymer Engineering and Science,1992, 32(11):732-742
[93]  Sarkar P,Gupta S K.Dynamic simulation of propylene polymerization in continuous flow stirred tank reactors[J].Polymer Engineering and Science,1993,33(6):368-374
[94]  Sato C,Ohtani T,Nishitani H.Modeling,simulation and nonlinear control of a gas-phase polymerization process[J].Computers & Chemical Engineering,2000,24(2):945-951 target="_blank">
[95]  Adilson J A,Rubens M F.Soft sensors development for on-line bioreactor state estimation[J].Computers & Chemical Engineering,2000,24(7):1099-1103 --- unreasonable DOI found: doi=Computers target="_blank">
[96]  Kresta J V,Marlin T E,MacGregor J F.Development of inferential process models using PLS[J].Computers & Chemical Engineering,1994,18(7):597-611 target="_blank">
[97]  Bhavik R B.Multiscale PCA with application to multivariate statistical process monitoring[J].AIChE Journal,1998,44(7):1596-1610
[98]  Mejdell T,Skogestad S.Composition estimator in a pilot-plant distillation column using multiple temperature[J].Industrial & Engineering Chemistry Research,1991,30(12):255-2564 --- unreasonable DOI found: doi=Industrial target="_blank">
[99]  Zita I T,Mathieu S,Gerrit V S,et al.Assessment of near infrared and software sensor for biomass monitoring and control[J].Chemometrics and Intelligent Laboratory Systems,2008,94(2):166-174
[100]  Jose C,Jesus P,Alberto F.Bilinear modeling of batch processes(Ⅰ):Theoretical discussion[J].Journal of Chemometrics,2008,22(5):299-308
[101]  Jose C,Jesus P.Bilinear modeling of batch processes(Ⅱ):A comparison of PLS soft-sensors[J].Journal of Chemometrics,2008,22(10):533-547
[102]  Rand E,Hector B,Christine M,et al.Fluorescence-based soft-sensor for monitoring beta-lactoglobulin and alpha-lactalbumin solubility during thermal aggregation[J].Biotechnology and Bioengineering,2008,99(3):567-577
[103]  Rumana S,Uttandaraman S,Sirish S,et al.Inferential sensors for estimation of polymer quality parameters:industry application of a PLS-based soft sensor for a LDPE plant[J].Chemical Engineering Science,2006,61(19):6372-6384
[104]  Bao L,Bodil R,Jorgen K H,et al.A systematic approach for soft sensor development[J].Computers & Chemical Engineering,2007,31(5):419-425 target="_blank">
[105]  Kourti T.Process analysis and abnormal situation detection:from theory to practice[J].IEEE Control Systems Magazine,2002,22(5):10-25
[106]  Li W,Yue H H,Valle C S,et al.Recursive PCA for adaptive process monitoring[J].Journal of Process Control,2000,10(5):471-486
[107]  Wang S,Cui J.Sensor-fault detection,diagnosis and estimation for centrifugal chiller systems using principal-component analysis method[J].Applied Energy,2005,82(3):197-213
[108]  Qin S J.Recursive PLS algorithms for adaptive data modeling[J].Computers & Chemical Engineering,1998,22(4):503-514 target="_blank">
[109]  Dayal B S,MacGregor J F.Recursive exponentially weighted PLS and its applications to adaptive control and prediction[J].Journal of Process Control,1997,7(3):169-179
[110]  Ruta D,Gabrys B.An overview of classifier fusion methods[J].Computing and Information Systems,2000,7(1):1-10

Full-Text

Contact Us

service@oalib.com

QQ:3279437679

WhatsApp +8615387084133