基于现代非线性信息处理技术的气固流化床流型识别方法与实验研究
|
摘要
气固流化床是化工、能源等生产过程中的重要装置，在流化床建模、设计、开发和运行中需要获取流化床的流型和流型转换的信息。这对提高流化床的性能和传热、传质效率至关重要，流型参数的检测与识别一直是气固两相流参数监测的重要研究内容。
气固流化床压力脉动时间序列隐含着包括流型和过渡流型在内的两相流系统的动态行为信息，由于气固流化床在很宽的操作系统范围内是一个复杂的非线性时变系统，因此，本文采用现代非线性信息处理技术来进行流化床压力脉动信号的特征提取与流型识别方法的研究。以期能从新的角度更深入地认识流态化规律，探索流化床流型识别的新技术与新方法。
本文在大量实验数据基础上，将现代非线性信息处理方法包括希尔伯特黄变换(Hilbert-Huang Transform简写HHT)，互信息和信息传输以及模糊信息融合理论，首次应用到气固流化床压力脉冲时间序列的分析中，从理论和实验两个方面，系统地探讨了流化床流型的非线性识别原理，提出和实现了适合于工业现场和实验研究的三种流型识别方法。
首先采用非平稳、非线性信号处理的HHT变换，从压力脉动信号中提取一族内禀模态函数(IMFs)，建立时间—频率—能量三维希尔伯特黄谱图，从中发现了流型的转换与能量分布之间的联系；并进一步在实验研究中，计算得到了压力脉动信号不同阶次IMF能量转移与流型的定量关系。据此，提出了基于IMFs能量转移和不同频段能量分布的流型识别方法，该方法分析速度很快，具有十分良好的工程应用前景。
在讨论了相空间重构技术、复杂性参数算法和互信息理论基础上，计算了流化床系统内不同测点之间两两压力脉动信号之间的互信息传输时间序列，建立了以复杂性测变参数为其元素的信息传输矩阵(Information Transform Matrix简写ITM)，进一步定义了基于系统信息传输的信息传输平均值MITM(Mean of ITM)参数来表征气固流化床在不同流化状态时信息传输量的大小。
为了研究和识别流化床系统内的过渡流型，本文依据过渡流型的模糊性，在实验数据统计基础上应用模糊集理论，建立了不同过渡流型相对于确定性流型的隶属度函数。首次将过渡流型进行了量化，并采用模糊信息融合技术对多个特征参数和多个传感器信息进行特征层和决策层融合，提高了流型识别的准确率。从理论上和技术上为气固流化床流型和过渡流型的识别提供了新方法。
最后为使研究的流型识别方法能在实验室和工业现场得到应用，本文提出了流化床流型检测与识别系统的硬件和软件设计方案，并完成了三种非线性流型识别方法的应用软件包的编程与设计，为研究成果的应用打下了基础。
Gas-solid fluidized beds have been assumed as important equipment in the production process in chemical and energy industry. Information of flow regimes and their transition is needed in the model building, design, research and development due to the importance of improving the performance of fluidized beds and increasing the heat transfer rate and mass transfer rate. The detection or identification of the parameters characterizing different flow regimes has long been a significant topic in the parameter measurement of two-phase system.
Pressure fluctuation time series in gas-solid fluidized beds contain a lot of dynamic information, such as the information of flow regimes and transition states. Since gas-solid fluidized beds are a complex nonlinear time-varying system under wide operation, nonlinear theory is adopted and implemented to extract the characters of pressure fluctuation time series in gas-solid fluidized beds and find the new way to flow regime identification. Some new technologies and new ideas about the flow regime identification are discussed in this paper so as to cognize the fluidization from a new viewpoint in depth.
Based on a large amount of experimental data, nonlinear analysis, such as Hilbert-Huang Transform (HTT), mutual information and fuzzy information fusion theory, are used in the time series analysis of pressure fluctuation in gas-solid fluidized beds for the first time. Application of nonlinear theory to the flow regime identification is discussed systematically from the aspects of theory and experiment. Finally, three kinds of regime-identification methods are proposed and proved to be suitable for using in practical industrial fields and experimental studies.
In this study for the first time, the Hilbert-Huang Transform (HHT) is applied to analysis of the pressure-fluctuation in gas-fluidized beds. By using this new nonlinear and non-stationary signal-processing method, the Intrinsic Mode Functions (IMFs) are extracted from the pressure fluctuation signals and the time-frequency-energy distribution called Hilbert spectrum is established. From the spectrum the relationship between the flow transition and the energy distribution can be found. With the following study, the corresponding relations of the energy-transmission between different orders of Intrinsic Mode Functions (IMFs) under different flow states are obtained. Based on it, a new method, with which the energy-transmission between IMFs of pressure fluctuations and
the energy distribution in different IMFs can be used to detect the flow regime identification, is formed in this study. Because of the speed of analyzing by the new method, the prospect of its application to engineering will be fine.
After the discussion of phased-space reconstruct technology, complexity parameter algorithm and mutual information theory, the mutual information of different time serials from different sensors at different regimes in gas-solid fluidized beds are calculated. The fluctuate complexity of those mutual time information are got, and then the Information Transform Matrix (ITM) is obtained. Further more, the Mean of ITM (MITM) is applied to defining the identification of different fluidized regimes.
According to the previous study, transition states between different flow regimes in gas-solid fluidized beds show with obvious fuzzy characteristics. In this paper, fuzzy theory is implemented to identify the transition states in gas-solid fluidized beds. Membership functions are established to represent the membership grade of transition states for deterministic flow regimes. Transition states are quantified with fuzzy language and applying the fuzzy information fusion theory, multi parameters delivered from separated sensors are fused at characteristic level and multi decisions of each sensor are fused at the decision level. The experimental results indicate that the identification rate of flow regimes is improved. The fuzzy information fusion technology provides a new way to identify the transition states.
Finally, for ap
气固流化床压力脉动时间序列隐含着包括流型和过渡流型在内的两相流系统的动态行为信息，由于气固流化床在很宽的操作系统范围内是一个复杂的非线性时变系统，因此，本文采用现代非线性信息处理技术来进行流化床压力脉动信号的特征提取与流型识别方法的研究。以期能从新的角度更深入地认识流态化规律，探索流化床流型识别的新技术与新方法。
本文在大量实验数据基础上，将现代非线性信息处理方法包括希尔伯特黄变换(Hilbert-Huang Transform简写HHT)，互信息和信息传输以及模糊信息融合理论，首次应用到气固流化床压力脉冲时间序列的分析中，从理论和实验两个方面，系统地探讨了流化床流型的非线性识别原理，提出和实现了适合于工业现场和实验研究的三种流型识别方法。
首先采用非平稳、非线性信号处理的HHT变换，从压力脉动信号中提取一族内禀模态函数(IMFs)，建立时间—频率—能量三维希尔伯特黄谱图，从中发现了流型的转换与能量分布之间的联系；并进一步在实验研究中，计算得到了压力脉动信号不同阶次IMF能量转移与流型的定量关系。据此，提出了基于IMFs能量转移和不同频段能量分布的流型识别方法，该方法分析速度很快，具有十分良好的工程应用前景。
在讨论了相空间重构技术、复杂性参数算法和互信息理论基础上，计算了流化床系统内不同测点之间两两压力脉动信号之间的互信息传输时间序列，建立了以复杂性测变参数为其元素的信息传输矩阵(Information Transform Matrix简写ITM)，进一步定义了基于系统信息传输的信息传输平均值MITM(Mean of ITM)参数来表征气固流化床在不同流化状态时信息传输量的大小。
为了研究和识别流化床系统内的过渡流型，本文依据过渡流型的模糊性，在实验数据统计基础上应用模糊集理论，建立了不同过渡流型相对于确定性流型的隶属度函数。首次将过渡流型进行了量化，并采用模糊信息融合技术对多个特征参数和多个传感器信息进行特征层和决策层融合，提高了流型识别的准确率。从理论上和技术上为气固流化床流型和过渡流型的识别提供了新方法。
最后为使研究的流型识别方法能在实验室和工业现场得到应用，本文提出了流化床流型检测与识别系统的硬件和软件设计方案，并完成了三种非线性流型识别方法的应用软件包的编程与设计，为研究成果的应用打下了基础。
Gas-solid fluidized beds have been assumed as important equipment in the production process in chemical and energy industry. Information of flow regimes and their transition is needed in the model building, design, research and development due to the importance of improving the performance of fluidized beds and increasing the heat transfer rate and mass transfer rate. The detection or identification of the parameters characterizing different flow regimes has long been a significant topic in the parameter measurement of two-phase system.
Pressure fluctuation time series in gas-solid fluidized beds contain a lot of dynamic information, such as the information of flow regimes and transition states. Since gas-solid fluidized beds are a complex nonlinear time-varying system under wide operation, nonlinear theory is adopted and implemented to extract the characters of pressure fluctuation time series in gas-solid fluidized beds and find the new way to flow regime identification. Some new technologies and new ideas about the flow regime identification are discussed in this paper so as to cognize the fluidization from a new viewpoint in depth.
Based on a large amount of experimental data, nonlinear analysis, such as Hilbert-Huang Transform (HTT), mutual information and fuzzy information fusion theory, are used in the time series analysis of pressure fluctuation in gas-solid fluidized beds for the first time. Application of nonlinear theory to the flow regime identification is discussed systematically from the aspects of theory and experiment. Finally, three kinds of regime-identification methods are proposed and proved to be suitable for using in practical industrial fields and experimental studies.
In this study for the first time, the Hilbert-Huang Transform (HHT) is applied to analysis of the pressure-fluctuation in gas-fluidized beds. By using this new nonlinear and non-stationary signal-processing method, the Intrinsic Mode Functions (IMFs) are extracted from the pressure fluctuation signals and the time-frequency-energy distribution called Hilbert spectrum is established. From the spectrum the relationship between the flow transition and the energy distribution can be found. With the following study, the corresponding relations of the energy-transmission between different orders of Intrinsic Mode Functions (IMFs) under different flow states are obtained. Based on it, a new method, with which the energy-transmission between IMFs of pressure fluctuations and
the energy distribution in different IMFs can be used to detect the flow regime identification, is formed in this study. Because of the speed of analyzing by the new method, the prospect of its application to engineering will be fine.
After the discussion of phased-space reconstruct technology, complexity parameter algorithm and mutual information theory, the mutual information of different time serials from different sensors at different regimes in gas-solid fluidized beds are calculated. The fluctuate complexity of those mutual time information are got, and then the Information Transform Matrix (ITM) is obtained. Further more, the Mean of ITM (MITM) is applied to defining the identification of different fluidized regimes.
According to the previous study, transition states between different flow regimes in gas-solid fluidized beds show with obvious fuzzy characteristics. In this paper, fuzzy theory is implemented to identify the transition states in gas-solid fluidized beds. Membership functions are established to represent the membership grade of transition states for deterministic flow regimes. Transition states are quantified with fuzzy language and applying the fuzzy information fusion theory, multi parameters delivered from separated sensors are fused at characteristic level and multi decisions of each sensor are fused at the decision level. The experimental results indicate that the identification rate of flow regimes is improved. The fuzzy information fusion technology provides a new way to identify the transition states.
Finally, for ap
引文
[1] 陈学俊．“迅速发展中的一门新兴交叉学科—多相流热物理的进展”．《西安交通大学学报》Vol．30，No．4：9-17，1996．
[2] Tamarin, A. I. "The Origin of Self-Excited Oscillations in Fluctuation in Fluidized Beds". Int. Chem. Eng. 4:50, 1964.
[3] Lirang, R. & H. Littman. "Statistical Study of the Pressure Fluctuations in a Fluidized Bed". AIChE Symp. Ser., 67(116):11, 1971.
[4] Kang, W. K., J. P. Sutherland & G. L. Osberg. "Pressure Fluctuations in a Fluidized Bed with and without Screen Cylindrical Packings". In&EC Funmental, 6:499-504, 1967.
[5] Fan, L. T., et al. "Pressure Fluctuations in a Fluidized Bed".AIChE J., 27(3): 388-396, 1981.
[6] van der Schaaf, J., J. C. Schouten & C. M. van den Bleek. "Origin, Propagation and Attenuation of Pressure Waves in Gas-Solid Fluidized Beds". Powder Technology, 95:220～233, 1998.
[7] 蔡平等．“采用凝聚函数法对气固密相流化床流型转变过程的研究”．《化工学报》4：154-160，1989．
[8] Stringer, J. "Is a Fluidized Bed a Chaotic Dynamic System". Proc. Int. Conf. On Fluidized Bed Combustion, New York, 265-272, 1989.
[9] Daw, S., et al. "Chaotic Characteristics of a Complex Gas-solids Flow". Physical Review A, 41(2): 1179-1181,1990.
[10] Van Den Bleek, M. & J. C. Schouten. "Deterministic Chaos: a New Tool in Fluidized Design and Operation". Chem. Eng. J., 53: 75-87, 1993.
[11] Marzocchella, A. et al. "Chaotic Behavior of Gas-Solids Flow in the Riser of a Laboratory-Scale Circulating Fluidized Beds". AIChE J., 43(6): 1458-1468, 1997.
[12] Norden.E Huang et,al. "The Empriical Mode Decomposition and Hilbert Spectrum for Nonliner and Non-stationary Time Series Analysis".Proc.R.soc.Lond.A. 903-995, 1998.
[13] 陈甘棠，王樟茂．《多相流反应工程》，浙江大学出版社，1996．
[14] Wang Naining, Xu Guangdong. "On-line Measurements of the Solid-Gas Two Phase Flow Using Optical Technique", ISMTMF,127-132,1995
[15] Lynch G.F., Segal S.L. "Direct Measurement of the Solid Fraction of a Two-phase Fluid by Unclear Magenatic Resonance". Int.J.of Mass Transfer. Vol.20,No.1: 7-14, 1997
[16] Couthard. J.and Yan Y., "Ultrasonic Cross-correlation Flowmeter", Measurement and Control. Vol.26.1993
[17] Magda, J. J. et al. "Ultrasonic technique for monitoring the interface in multi-layer polymer flows". Processing Annual Technical Conference - ANTEC, Brookfield, 1182-1186, 1996.
[18] Fiedler, O.etal. "Usage of the Spatial Filter Method for Measurements of Local". Conference-ANTEC.1182-1186, 1996.
[19] Banerjee S.,and Lahey R.T., "Advance in Two-phase Flow Instrumentation." Advance Nuclear Science Technology, Vol, 13, 227-414, 1981.
[20] Gupta, G. "Flow visualization study in porous media using X-rays". Steel Research, 68(10): 434-440,1997.
[21] Bachalo,W.D., "Experimental Methods in Multiphase Flows", ISA Trans. 33.171-197,1994.
[22] Peyton A.J.et.al. "Particle Velocities in Multiphase Flows" IEE Colloquium(Digest). Stevenage,1996.
[23] 徐芩安．《关于过程层析成像技术的评述 多相流检测技术进展》 石油工业出版社，7-12，1996．
[24] Futao Zhao, Jing Ou, et al, "Pattern-Based Fuzzy Predictive Control for a Chemical Process with Deadline." Engineering Applications of Artifical Intelligence. 13CD:37-45, 2000.
[25] Qu Jing .et. al. "Application of Artifical Neural Network to Measurement of Gas-solid Two Phase Flowrate". Proc.of 3rd. Int.Symposium on Multiphase Flow and Heal Transfer. 1364-1368, 1994.
[26] Chen Gong., et al. " Application of Wavelets transform to flow regines". Proceeding of FLOMEKO.Beijing, Oce. 410-415,1996.
[27] Bakshi.B.R.,H.Zhong, et al. "Analysis of Flow in Gas-liquid Bubble Columns Using
Multi-Resolution Methods".Trans.Icheme. 73-68,1995.
[28] Bai, D., H. T. Bi & J. R. Grace. Chaotic Behavior of Fluidized Beds Based on Pressure and Voidage Fluctuations. AIChE Journal, 43(5):1357-1361,1997.
[29] Clough, D. E., & D. C. Gyure. Stochastic Inferential Control of the Fluidized State via Differential Pressure Measurements. Chem. Eng. Commun, 28:59-71, 1984.
[30] Kai, T. & S. "Furusaki. Methanation of Carbon Dioxide and Fluidization quality in a Fluid Bed Reactot—the Influence of a decrease in Gas Volume". Chem. Eng. Sci., 42(2):335-339, 1987.
[31] Chong, Y. O., et al.. "Control of the Quality of Fluidization in a Tall Bed Using the Variance of Pressure Fluctuations". Powder Technology, 53: 237-246, 1987.
[32] Nelson, B. H., C. L. Briens & M. A. Bergougnou. Pressure Fluctuations at Individual Grid Holes of a Gas-Solid Fluidized Bed. Powder Technologic, 77:95-102,1993.
[33] Svoboda, K. et al. "Influence of Particle Size on the Pressure Fluctuations and Slugging in a Fluidized Bed". AIChE J., 30(3):513-517, 1984.
[34] Neogi, D. et al. "Effect of superficial Velocity on Pressure Fluctuations in a Gas-Solid Fluidized Bed: a Stochastic Analysis". Applied Stochastic Models and Data Analysis, 4: 13-34, 1988.
[35] Kage, H., et al. "Frequency Analysis of Pressure Fluctuation in Fluidized Bed Plenum". Journal of Chemical Engineering of Japan, 24(1): 76-81,1991.
[36] Yashima, M. et al. "Stochastic Modeling of Pressure Fluctuations in a Three-Phase Fluidized Bed". AIChE J., 38(4):629-634, 1992.
[37] Lao, L. Y., Zhang H. J. & Li H. Q. "The Relationships Between the WVD Characteristics of Pressure Drop and Gas-Liquid Two-Phase Flow Patterns in Horizontal Pipeline". Proceedings of ISMTMF'98, Beijing, 1998.
[38] He, Z., et al. "Pressure-Fluctuation Analysis of a Gas-Solid Fluidized Bed Using the Wigner Distribution". AIChE J., 43(2): 345-355, 1997.
[39] 黄志尧等．“分形技术与小波分析在气固流化床研究中的应用”．《东北大学学报》(自然科学版)，21(S1)：194-197，2000．
[40] Ling,Z. et.al. "Wavelet Analysis of Pressure Fluctuation signal in a Gas-solid Fluidized Bed " 《Journal of Zhejiang University》 SCIENC, 2002(1):265-272,2002.
[41] Pence, V. & D. E. Beasely. "Chaos Suppression in Gas-Solid Fluidization". Chaos, 8(2): 514-519,1998.
[42] 陈伟等．“加压流态化Ⅲ 压力脉动与分形研究”．《化学反应工程与工艺》14(1)：14-20，1998．
[43] 黄轶轮，陈伯川等．“气固流化床压力脉动信号的混沌特征分析”．《化学反应工程与工艺》．16(4)：357-362,2000．
[44] Fan, L. T., et al. "Stochastic Analysis of a Three-Phase Fluidized Bed: Fractal Approach". AIChE J. 36(10): 1529-1535, 1990.
[45] Kwon, H. W. et al. "Bubble-Chord Length and Pressure Fluctuations in Three-Phase Fluidized Beds". Ind. Eng. Chem. Res., 33(7): 1852-1857,1994.
[46] 赵贵兵等．“气固流化床压力波动信号成分分析“．《东北大学学报》(自然科学版)．21(S1)：25-28，2000．
[47] Lempel, A. & J. Ziv. "Complexity of Finite Sequences", IEEE Transactions on Information Theory, 22(1): 75-81,1976.
[48] Grassberger, P. "How to Measure Self-Generated Complexity". Physica 140A:319-325,1986.
[49] 李素兰．《脑电时间序列分析的非线性动力学方法》浙江大学硕士论文，1998．
[50] Priestley, M.B. "Spectral Analysis and Time Series". London:Academic Press. 1981.
[51] 陈伟等．“加压流化床中差压脉动时间序列的复杂性”．《化工学报》48(6)：746-750,1997．
[52] 黄蓓、陈伯川、黄轶伦等．“算法复杂性在气固流化床动力学中的多尺度分析”．《化工学报》 53(12)：509-613，2002．
[53] 黄春燕、陈伯川等．“涨落复杂性在气固流化床压力信号分析中的运用”．《仪器仪表学报》 22(3)：76-80，2001．
[54] 陈伯川、黄蓓等．“三种复杂性测量度在气固流化床压力脉动中的应用”．《高校化学工程学报》16(4)：154-159，2002．
[55] Yerushalmi, J. & N. T. "Cankurt. Further Studies of the Regimes of Fluidization". Powder
Technology, 24:187-205,1979.
[56] 蔡平等．“鼓泡流态化向湍动过渡的判别”．《化工学报》4：391-401，1986．
[57] Lee, G. S. & S. D. Kim. " Pressure Fluctuations in Turbulent Fluidized Beds". Chem. Eng. Jpn.21(5):515-521,1988.
[58] 阳永荣等．“湍动流化床的流型与流型过渡”．《化学反应工程与工艺》6(2)：9-16，1990．
[59] Chen, G. et al. "Flow Regime Identification Based on Wavelets Transform". Proceedings of ISMTMF'98, Beijing,1998.
[60] 黄轶伦．《气体流床压力脉冲序列的非线性分析与实验研究》浙江大学博士论文．2001
[61] Huang S.M. et al. "Tomographie Imaging of Industrial Process Equipment:Techniques and Applications." Jphys.E.22(3): 173-177,1989.
[62] Wang S.J and Dyakowski,T. et al. "Real Time Capacitance Imaging of Bubble Formation at the Distribution of a Fluidized bed". The Chemical Engineering Journal 56:95-100,1995.
[63] 黄志尧等．“层析成像技术在多相流检测中的应用”．《化学反应工程与工艺》 12(4)：395-405，1996．
[64] Vinegar H.J. et al. "Tomographic Imaging of Three-phase Flow Experiments". Rev SCI. lnstrum. Vol.58: 96,1987.
[65] Abdullah M.Z. "Electrical Impedance TomoGraphy for Imaging Conducting Mixtures in Hydrocyclence Separators ." Ph.D. Thesis, VMISt,Manchester, UK, 1993
[66] Wolf, J. "Investigation of bubble flow by Ultrasonic Tomography". Part.Part.Syst.Charaet, Vol 5:170-173,1988.
[67] Xu L.A. et al. "Investigation of Transmission-Model UCT System for Bubbly Gas/Ligiod Fluid Distribrition Monitoring ". in proc.of ECATP'93. Karlsruhe,Germarny.209-212,1993.
[68] Dickin,F.J,Hoyle,B.S.etal."Tomographie Imaging of Industrial Process Equipment:Techniques. and Application". IEE Proceeding-G. 139(1):72-82,1992.
[69] Drahos, J., F. Bradka & M. Puncoehar. "Fractal Behaviour of Pressure Fluctuations in a Bubble Column". Chem. Eng. Sci, 47(15): 4069-4075, 1992.
[70] Karamavruc, A. I. & N. N. Clark. "Local Differential Pressure Analysis in a Slugging Bed
Using Deterministic Chaos Theory. Chem. Eng. Sci., 52(3):357-370, 1997.
[71] Loh CH ,et.al. "Aplication of the Empirical Mode Decomposition-Hilbert Spectrum Method to Identify Near-fault Ground-motion Characteristics and Structural Responses[J]". Bulletin on the serimological Society of Americ. (91):1339-1357, 2001.
[72] Vasudvan K,et.al. "Emperical Mode Skeletonization of Deep Crustal Seismic Data:Theory and Applocations[J]". Journal of geophysical Reserarch-Solid earth. 2001 (105):7845-7856, 2001.
[73] Echererria,J.C.,et.al. "Application of Empirical Mode Decomposition to Heart Rate Variability Analysis [J]". Medical &Biological Engieering &Computing. (39):471-479, 2000.
[74] 赵犁丰等．“基于经验模式分解的希尔伯特变换包络提取在机械故障诊断中的应用”．《青岛海洋大学学报》32(6)，965-970，2002．
[75] Huang, NE. et al. "The empirical mode decompositon and the Hilbert spectrum for nonlinear and non-stationary time series analysis". NASA Patent Document. 235-258, 1996.
[76] Huang, NE. et al. "A new method for nonlinear and non-stationary time series analysis". Proc. of 4~(th) Int. Conf on Stochastic Structural Dynamics, Notre Dame(Indiana), USA, Aug. 1998. Stochastic Structural Dynamics, Balkema, Rotterdam, Holand, 559-564, 1999.
[77] Reginald N. Meeson. "Calculating the Hilbert/Huang Transform in Real Time". Institute for Defense Analyses Alexandria, VA 22311, USA meeson@ida.org
[78] He, Z., et al. "Modeling Pressure Fluctuations via Correlation Structure in a Gas-Solids Fluidized Bed". AIChE J., 43(7): 1914-1920, 1997.
[79] 凌复华．《非线性动力学系统的数值研究》，上海交通大学出版社，1989．
[80] Takens, F. "Lectures Notes in Mathematics". Berlin:Springer-Verlag, 1980.
[81] Grassberger, P. & I. Procaccia. "Characterization, of Strange Attractors". Physical Review Letters, 50(5): 346-349, 1983.
[82] 汪富泉，罗朝盛，陈国先．“G-P算法的改进及其应用”．《计算物理》，10(3)：345-350，1993．
[83] Fraser, A. M. "Information and Entropy in Strange Attractors". IEEE Transactions on Information Theory, 35(2): 244-262, 1989.
[84] Wolf, A., et al. "Determining Lyapunov Exponents from a Time Series". Physica 16D: 285-317,
1985.
[85] Gao, J. & Z. Zheng. "Local Exponential Divergence Plot and Optimal Embedding of a Chaotic Time Series". Physics Letters A, 181(2): 153-158, 1993.
[86] 赵贵兵等．“周期信号对计算流化床动力学重构滞时的影响”．《化工学报》51(3)：331-337，2000．
[87] Tsonis, A. A. "Chaos from Theory to Applications". New York: Plenum Press, 1992.
[88] Shaw, R. "Strange Attractors, Chaotic Behavior and Information Flow". Z. Naturforsch, 36A(1); 88-112, 1981.
[89] Fraser, M. & H. L. Swinney. "Independent Coordinates for Strange Attractors from Mutual Information". Physical Review A, 33(2): 1134-1140, 1986.
[90] Grassberger P. "Toward a Quantitative Theory of Self-Generated Complexity". Int. J. Theor. Phys. 25:907-938, 1986.
[91] Koppel H, Atlan H. "Program-length Complexity, Sophistication and Induction". Inform. Sci., 56:186-213, 1991.
[92] Huberman, B. A. & T. Hogg. "Complexity and Adaptation". Physica D. 22:376-384, 1986.
[92] Kasper, F. & H. G. Schuster. "Easily Calculable Measure for the Complexity of Spatiotemporal Patterns". Phy. Rev. A, 36(2):842-848, 1987.
[94] 刘式达，刘式适．《非线性动力学和复杂现象》，气象出版社，1989．
[95] Wackerbauer, R., et al. A Comparative Classification of Complexity Measures. Chaos, Solitons & Fractals, 4(1): 133-173, 1994.
[96] Atmanspacher, H. et al. "Complexity and Meaning in Nonlinear DynamicaI Systems". Open Systems & Information dynamic, 1:269-289, 1991.
[97] Wackerbauer, R., et al. "A Comparative Classification of Complexity Measures". Chaos, Solitons & Fractals, 4(1): 133-173, 1994.
[98] 孟庆生．《信息论》，西安交通大学出版社，1986．
[99] 金振玉．《信息论》，北京理工大学出版社，1991．
[100] Vastano J A and Swinney H L. "Information Transport in Spatiotemporal Systems[J]". Phys Rev Lett, 1988, 60(18):1773-1776
[101] 王晓萍，黄轶轮．“气固流化床多传感器信息传输的复杂性研究”．《高校化学工程学报》10：585-590，2003．
[102] 黄轶伦，汪乐宇，郑燕萍等．“气固流化床中信息熵的实验研究”．《高校化学工程学报》15(20)：167-173，2002．
[103] 徐京华，童勤业，刘仁．“大脑皮层信息传输和精神分裂症”．《生物物理学报》12(1)：103-108，1996．
[104] 甄玲．《气固流化床信息传输特性及其应用研究》浙江大学硕士论文，2002．
[105] 王晓萍，黄轶轮．“气固流化床信息传输和流型识别”．《化工学报》8：1059-1064，2003．
[106] 蔡希尧．“多源信息融合”．《电子科学技术评论》．1990，(3)．
[107] 康耀红，蔡希尧等．“多传感器数据融合现状综述”．《电子科技大学学报》．计算机专辑，1994．
[108] 周章玉，石福炎．“由压力波动判断气—固流化床中的流化类型”．《化学反心工程与工艺》．15(3)：262-267,1999．
[109] 彭黎辉，张宝芬等．“基于模糊神经元网络的两相流流型辨识方法”．《模式识别与人工智能》．10(4)：332-337，1997．
[110] 赵贵兵等．“散式流态化到聚式流态化的混沌识别”．《化工学报》51(4)：468-479,2000．
[111] J Linas. "A Surrvey of Techniques for CIS Data Fusion". SAIC.ProcVIEE C~3I Conf Bournemouth.
[112] 美国国防部关键技术计划(1992年)。北京：国防科技信息中心，1993．
[113] 郁文贤、雍少为等．“多传感器信息融合技术述评”《国防科技大学学报》16(3)：1-11，1994．
[114] Edward Waltz,James Llians.《多传感器数据融合》赵宗贵等译，电子部28所．
[115] A R June. "A Framework for Automatede Tactical Data Fusion". Fournal of Robotic Systems 7(3):337～372, 1990.
[116] 冀海峰，黄志尧等．“基于信息融合技术的气固流化床流型辨识”．《仪器仪表学报》增刊，23(3)：897-899，2002．
[117] D C A Thomopoulos. "Sensor Integration and Data Fusion". Journal of Robotic Systems 7(3):337～372, 1990.
[118] Pemberton W, et al. "A context dependent automatic target recognize system". Proc.SPIE. Vol,485,May 1984.
[119] P S Charvez. "Digital Merging of Landsat TM and. Digitized NHAP Data for 1:2400 Scale Image Mapping". PERS, 52 (10) 1637-1645, 1986.
[120] Bar-Shalom. "Multitarget—Multisensor Tracking: Adacanced Application". 1987.
[121] Ted J Broida.Performanee "Prediction for Multi-sensor Tracking Systems: Kinematic Accurcay and data Performance". SPIE Vol. 1198.Sensor Fusion Ⅱ, 156-169, 1989.
[122] S S Blackman. "Multiple-target Tracking with Redar Applications". Artech House, Norwood, Masachustts, 1986.
[123] R Johnson. "Automatic Target Recognition Fuse Sensors and Artificial Intelligence". Defense Electronics, 1:106～115, 1984.
[124] R C Luo,et al. "A hierarchical Target Representation for Autonomous Recognition Using Distributed Sensors". Proc. SPIE Conf On Sensor Fusion Ⅲ, 537, 1989.
[125] E Walt. Data "Fusion for C3I Systems". C31 Handbook, EW communication, Palo Altom, Calfornia, 24-29, 1986.
[126] S C A Thomopoulos, et al. "Optimal Decision Distributed Decision Fusion. IEEE Trans". On Aerospace and Electronic Systems, 25(6), 1989.
[127] M A A bidi. "Sensor Fusion: a New Approach and Its Approach and Its Application". In Proc SPIE Conf On sensor Fusion Ⅱ. 235-346, 1989.
[128] H F Durrant-Whyte. "Consistent Integration and Propagation of Disparate Sensor Observation". Inter Journal of Robotics Research, No. 6(3):3～24, 1987.
[129] T P Garey, et al. "An Inference Technique for Integration Knowledge from Disparate Source". Proc the Inter. Joint Conf on Artificial Intelligence, Vancouver, August 319～325, 1981.
[130] E L Waltz, D M Buede. "Data Fusion and Decision Support for Command and control". IEEE Trans. On SMC, 616:865～879, 1986.
[131] Lang hong, et.al. "Recursive Temporal-Spatial Information Fusion with Applications to Target
Identification". IEEE Trans. On Aerospace and Electronic Systems, 29(2):435～445, 1993.
[132] S C A Thomopoulos. "Sensor Integration and Data Fusion". J Robstic Syst. 7(3):337-372 1990.
[133] 李安贵等．《模糊数学及其应用》北京科技大学出版社．1994．
[134] T L Huntsherger, et al. "A Framework for Multisensor Fusion in the Presence of Uncertainty". Proc. Of Workship on Spatial Reasoning and Multi-sensro Fusion, St. Charles, I Ⅲ I, Oct. 345-350, 1987.
[135] S K Rogers. Et.al. "Artificial Neutral Netwrok Technology for Automatuic Target Recognition". SPIE InstituteSeries Vol. IS 7, 231～247, 1990.
[136] 张兆礼等．“无损检测中的基于模糊神经网络数据融合技术”．《电子测量与仪器学报》 15(1)：58-62,2001
[137] 张立明．《人工神经网络的模型及其应用》复旦大学出版社．1993．
[138] 黄串福等．《模糊信息优化处理技术及其应用》 北京航空航天大学出版社．1995．
[139] 汪培庄．《模糊集合论及其应用》上海科学技术出版社 1983．
[140] Zadeh. L. A, Fuzzy sets[J], Information and Control,1965(8),338～35.
[141] 康耀红．《数据融合理论与应用》 西安电子科技大学出版社．1997．
[142] 有本卓著．杨逢春译．近代信息论．北京：人民邮电出版社，1985
[143] 孙涛、张宏建等，基于模糊逻辑融合算法的气液两相流流型辨识方法，仪器仪表学报，2001．6，22(3)：P293-294。
[144] Coifman R R. Wickerhauser M V. "Entropy—Based Algorithms for Best Basis Selection". IEEE Transactions on Information Theory, 1992.38(2):713-718.
[145] 王晓萍等．“多传感器数据融合在气固流化床流型识别中的应用”《化工学报》，待发表。
[146] 孙尚拱等．《实用判别分析》科学出版社．1990．
[147] E Waltz. J Linas. Multisensor Data Fusion, Arrech House. MA. 1990.
[148] 王晓东等．“模糊模式识别在流型判别中的应用”．《油气储运》 18(5)：15-18，1999．
[149] 陈国华．“模糊理论在焊缝缺陷质量等级评定中的应用研究”《无损检测》20(2)：39-41，1998．
[2] Tamarin, A. I. "The Origin of Self-Excited Oscillations in Fluctuation in Fluidized Beds". Int. Chem. Eng. 4:50, 1964.
[3] Lirang, R. & H. Littman. "Statistical Study of the Pressure Fluctuations in a Fluidized Bed". AIChE Symp. Ser., 67(116):11, 1971.
[4] Kang, W. K., J. P. Sutherland & G. L. Osberg. "Pressure Fluctuations in a Fluidized Bed with and without Screen Cylindrical Packings". In&EC Funmental, 6:499-504, 1967.
[5] Fan, L. T., et al. "Pressure Fluctuations in a Fluidized Bed".AIChE J., 27(3): 388-396, 1981.
[6] van der Schaaf, J., J. C. Schouten & C. M. van den Bleek. "Origin, Propagation and Attenuation of Pressure Waves in Gas-Solid Fluidized Beds". Powder Technology, 95:220～233, 1998.
[7] 蔡平等．“采用凝聚函数法对气固密相流化床流型转变过程的研究”．《化工学报》4：154-160，1989．
[8] Stringer, J. "Is a Fluidized Bed a Chaotic Dynamic System". Proc. Int. Conf. On Fluidized Bed Combustion, New York, 265-272, 1989.
[9] Daw, S., et al. "Chaotic Characteristics of a Complex Gas-solids Flow". Physical Review A, 41(2): 1179-1181,1990.
[10] Van Den Bleek, M. & J. C. Schouten. "Deterministic Chaos: a New Tool in Fluidized Design and Operation". Chem. Eng. J., 53: 75-87, 1993.
[11] Marzocchella, A. et al. "Chaotic Behavior of Gas-Solids Flow in the Riser of a Laboratory-Scale Circulating Fluidized Beds". AIChE J., 43(6): 1458-1468, 1997.
[12] Norden.E Huang et,al. "The Empriical Mode Decomposition and Hilbert Spectrum for Nonliner and Non-stationary Time Series Analysis".Proc.R.soc.Lond.A. 903-995, 1998.
[13] 陈甘棠，王樟茂．《多相流反应工程》，浙江大学出版社，1996．
[14] Wang Naining, Xu Guangdong. "On-line Measurements of the Solid-Gas Two Phase Flow Using Optical Technique", ISMTMF,127-132,1995
[15] Lynch G.F., Segal S.L. "Direct Measurement of the Solid Fraction of a Two-phase Fluid by Unclear Magenatic Resonance". Int.J.of Mass Transfer. Vol.20,No.1: 7-14, 1997
[16] Couthard. J.and Yan Y., "Ultrasonic Cross-correlation Flowmeter", Measurement and Control. Vol.26.1993
[17] Magda, J. J. et al. "Ultrasonic technique for monitoring the interface in multi-layer polymer flows". Processing Annual Technical Conference - ANTEC, Brookfield, 1182-1186, 1996.
[18] Fiedler, O.etal. "Usage of the Spatial Filter Method for Measurements of Local". Conference-ANTEC.1182-1186, 1996.
[19] Banerjee S.,and Lahey R.T., "Advance in Two-phase Flow Instrumentation." Advance Nuclear Science Technology, Vol, 13, 227-414, 1981.
[20] Gupta, G. "Flow visualization study in porous media using X-rays". Steel Research, 68(10): 434-440,1997.
[21] Bachalo,W.D., "Experimental Methods in Multiphase Flows", ISA Trans. 33.171-197,1994.
[22] Peyton A.J.et.al. "Particle Velocities in Multiphase Flows" IEE Colloquium(Digest). Stevenage,1996.
[23] 徐芩安．《关于过程层析成像技术的评述 多相流检测技术进展》 石油工业出版社，7-12，1996．
[24] Futao Zhao, Jing Ou, et al, "Pattern-Based Fuzzy Predictive Control for a Chemical Process with Deadline." Engineering Applications of Artifical Intelligence. 13CD:37-45, 2000.
[25] Qu Jing .et. al. "Application of Artifical Neural Network to Measurement of Gas-solid Two Phase Flowrate". Proc.of 3rd. Int.Symposium on Multiphase Flow and Heal Transfer. 1364-1368, 1994.
[26] Chen Gong., et al. " Application of Wavelets transform to flow regines". Proceeding of FLOMEKO.Beijing, Oce. 410-415,1996.
[27] Bakshi.B.R.,H.Zhong, et al. "Analysis of Flow in Gas-liquid Bubble Columns Using
Multi-Resolution Methods".Trans.Icheme. 73-68,1995.
[28] Bai, D., H. T. Bi & J. R. Grace. Chaotic Behavior of Fluidized Beds Based on Pressure and Voidage Fluctuations. AIChE Journal, 43(5):1357-1361,1997.
[29] Clough, D. E., & D. C. Gyure. Stochastic Inferential Control of the Fluidized State via Differential Pressure Measurements. Chem. Eng. Commun, 28:59-71, 1984.
[30] Kai, T. & S. "Furusaki. Methanation of Carbon Dioxide and Fluidization quality in a Fluid Bed Reactot—the Influence of a decrease in Gas Volume". Chem. Eng. Sci., 42(2):335-339, 1987.
[31] Chong, Y. O., et al.. "Control of the Quality of Fluidization in a Tall Bed Using the Variance of Pressure Fluctuations". Powder Technology, 53: 237-246, 1987.
[32] Nelson, B. H., C. L. Briens & M. A. Bergougnou. Pressure Fluctuations at Individual Grid Holes of a Gas-Solid Fluidized Bed. Powder Technologic, 77:95-102,1993.
[33] Svoboda, K. et al. "Influence of Particle Size on the Pressure Fluctuations and Slugging in a Fluidized Bed". AIChE J., 30(3):513-517, 1984.
[34] Neogi, D. et al. "Effect of superficial Velocity on Pressure Fluctuations in a Gas-Solid Fluidized Bed: a Stochastic Analysis". Applied Stochastic Models and Data Analysis, 4: 13-34, 1988.
[35] Kage, H., et al. "Frequency Analysis of Pressure Fluctuation in Fluidized Bed Plenum". Journal of Chemical Engineering of Japan, 24(1): 76-81,1991.
[36] Yashima, M. et al. "Stochastic Modeling of Pressure Fluctuations in a Three-Phase Fluidized Bed". AIChE J., 38(4):629-634, 1992.
[37] Lao, L. Y., Zhang H. J. & Li H. Q. "The Relationships Between the WVD Characteristics of Pressure Drop and Gas-Liquid Two-Phase Flow Patterns in Horizontal Pipeline". Proceedings of ISMTMF'98, Beijing, 1998.
[38] He, Z., et al. "Pressure-Fluctuation Analysis of a Gas-Solid Fluidized Bed Using the Wigner Distribution". AIChE J., 43(2): 345-355, 1997.
[39] 黄志尧等．“分形技术与小波分析在气固流化床研究中的应用”．《东北大学学报》(自然科学版)，21(S1)：194-197，2000．
[40] Ling,Z. et.al. "Wavelet Analysis of Pressure Fluctuation signal in a Gas-solid Fluidized Bed " 《Journal of Zhejiang University》 SCIENC, 2002(1):265-272,2002.
[41] Pence, V. & D. E. Beasely. "Chaos Suppression in Gas-Solid Fluidization". Chaos, 8(2): 514-519,1998.
[42] 陈伟等．“加压流态化Ⅲ 压力脉动与分形研究”．《化学反应工程与工艺》14(1)：14-20，1998．
[43] 黄轶轮，陈伯川等．“气固流化床压力脉动信号的混沌特征分析”．《化学反应工程与工艺》．16(4)：357-362,2000．
[44] Fan, L. T., et al. "Stochastic Analysis of a Three-Phase Fluidized Bed: Fractal Approach". AIChE J. 36(10): 1529-1535, 1990.
[45] Kwon, H. W. et al. "Bubble-Chord Length and Pressure Fluctuations in Three-Phase Fluidized Beds". Ind. Eng. Chem. Res., 33(7): 1852-1857,1994.
[46] 赵贵兵等．“气固流化床压力波动信号成分分析“．《东北大学学报》(自然科学版)．21(S1)：25-28，2000．
[47] Lempel, A. & J. Ziv. "Complexity of Finite Sequences", IEEE Transactions on Information Theory, 22(1): 75-81,1976.
[48] Grassberger, P. "How to Measure Self-Generated Complexity". Physica 140A:319-325,1986.
[49] 李素兰．《脑电时间序列分析的非线性动力学方法》浙江大学硕士论文，1998．
[50] Priestley, M.B. "Spectral Analysis and Time Series". London:Academic Press. 1981.
[51] 陈伟等．“加压流化床中差压脉动时间序列的复杂性”．《化工学报》48(6)：746-750,1997．
[52] 黄蓓、陈伯川、黄轶伦等．“算法复杂性在气固流化床动力学中的多尺度分析”．《化工学报》 53(12)：509-613，2002．
[53] 黄春燕、陈伯川等．“涨落复杂性在气固流化床压力信号分析中的运用”．《仪器仪表学报》 22(3)：76-80，2001．
[54] 陈伯川、黄蓓等．“三种复杂性测量度在气固流化床压力脉动中的应用”．《高校化学工程学报》16(4)：154-159，2002．
[55] Yerushalmi, J. & N. T. "Cankurt. Further Studies of the Regimes of Fluidization". Powder
Technology, 24:187-205,1979.
[56] 蔡平等．“鼓泡流态化向湍动过渡的判别”．《化工学报》4：391-401，1986．
[57] Lee, G. S. & S. D. Kim. " Pressure Fluctuations in Turbulent Fluidized Beds". Chem. Eng. Jpn.21(5):515-521,1988.
[58] 阳永荣等．“湍动流化床的流型与流型过渡”．《化学反应工程与工艺》6(2)：9-16，1990．
[59] Chen, G. et al. "Flow Regime Identification Based on Wavelets Transform". Proceedings of ISMTMF'98, Beijing,1998.
[60] 黄轶伦．《气体流床压力脉冲序列的非线性分析与实验研究》浙江大学博士论文．2001
[61] Huang S.M. et al. "Tomographie Imaging of Industrial Process Equipment:Techniques and Applications." Jphys.E.22(3): 173-177,1989.
[62] Wang S.J and Dyakowski,T. et al. "Real Time Capacitance Imaging of Bubble Formation at the Distribution of a Fluidized bed". The Chemical Engineering Journal 56:95-100,1995.
[63] 黄志尧等．“层析成像技术在多相流检测中的应用”．《化学反应工程与工艺》 12(4)：395-405，1996．
[64] Vinegar H.J. et al. "Tomographic Imaging of Three-phase Flow Experiments". Rev SCI. lnstrum. Vol.58: 96,1987.
[65] Abdullah M.Z. "Electrical Impedance TomoGraphy for Imaging Conducting Mixtures in Hydrocyclence Separators ." Ph.D. Thesis, VMISt,Manchester, UK, 1993
[66] Wolf, J. "Investigation of bubble flow by Ultrasonic Tomography". Part.Part.Syst.Charaet, Vol 5:170-173,1988.
[67] Xu L.A. et al. "Investigation of Transmission-Model UCT System for Bubbly Gas/Ligiod Fluid Distribrition Monitoring ". in proc.of ECATP'93. Karlsruhe,Germarny.209-212,1993.
[68] Dickin,F.J,Hoyle,B.S.etal."Tomographie Imaging of Industrial Process Equipment:Techniques. and Application". IEE Proceeding-G. 139(1):72-82,1992.
[69] Drahos, J., F. Bradka & M. Puncoehar. "Fractal Behaviour of Pressure Fluctuations in a Bubble Column". Chem. Eng. Sci, 47(15): 4069-4075, 1992.
[70] Karamavruc, A. I. & N. N. Clark. "Local Differential Pressure Analysis in a Slugging Bed
Using Deterministic Chaos Theory. Chem. Eng. Sci., 52(3):357-370, 1997.
[71] Loh CH ,et.al. "Aplication of the Empirical Mode Decomposition-Hilbert Spectrum Method to Identify Near-fault Ground-motion Characteristics and Structural Responses[J]". Bulletin on the serimological Society of Americ. (91):1339-1357, 2001.
[72] Vasudvan K,et.al. "Emperical Mode Skeletonization of Deep Crustal Seismic Data:Theory and Applocations[J]". Journal of geophysical Reserarch-Solid earth. 2001 (105):7845-7856, 2001.
[73] Echererria,J.C.,et.al. "Application of Empirical Mode Decomposition to Heart Rate Variability Analysis [J]". Medical &Biological Engieering &Computing. (39):471-479, 2000.
[74] 赵犁丰等．“基于经验模式分解的希尔伯特变换包络提取在机械故障诊断中的应用”．《青岛海洋大学学报》32(6)，965-970，2002．
[75] Huang, NE. et al. "The empirical mode decompositon and the Hilbert spectrum for nonlinear and non-stationary time series analysis". NASA Patent Document. 235-258, 1996.
[76] Huang, NE. et al. "A new method for nonlinear and non-stationary time series analysis". Proc. of 4~(th) Int. Conf on Stochastic Structural Dynamics, Notre Dame(Indiana), USA, Aug. 1998. Stochastic Structural Dynamics, Balkema, Rotterdam, Holand, 559-564, 1999.
[77] Reginald N. Meeson. "Calculating the Hilbert/Huang Transform in Real Time". Institute for Defense Analyses Alexandria, VA 22311, USA meeson@ida.org
[78] He, Z., et al. "Modeling Pressure Fluctuations via Correlation Structure in a Gas-Solids Fluidized Bed". AIChE J., 43(7): 1914-1920, 1997.
[79] 凌复华．《非线性动力学系统的数值研究》，上海交通大学出版社，1989．
[80] Takens, F. "Lectures Notes in Mathematics". Berlin:Springer-Verlag, 1980.
[81] Grassberger, P. & I. Procaccia. "Characterization, of Strange Attractors". Physical Review Letters, 50(5): 346-349, 1983.
[82] 汪富泉，罗朝盛，陈国先．“G-P算法的改进及其应用”．《计算物理》，10(3)：345-350，1993．
[83] Fraser, A. M. "Information and Entropy in Strange Attractors". IEEE Transactions on Information Theory, 35(2): 244-262, 1989.
[84] Wolf, A., et al. "Determining Lyapunov Exponents from a Time Series". Physica 16D: 285-317,
1985.
[85] Gao, J. & Z. Zheng. "Local Exponential Divergence Plot and Optimal Embedding of a Chaotic Time Series". Physics Letters A, 181(2): 153-158, 1993.
[86] 赵贵兵等．“周期信号对计算流化床动力学重构滞时的影响”．《化工学报》51(3)：331-337，2000．
[87] Tsonis, A. A. "Chaos from Theory to Applications". New York: Plenum Press, 1992.
[88] Shaw, R. "Strange Attractors, Chaotic Behavior and Information Flow". Z. Naturforsch, 36A(1); 88-112, 1981.
[89] Fraser, M. & H. L. Swinney. "Independent Coordinates for Strange Attractors from Mutual Information". Physical Review A, 33(2): 1134-1140, 1986.
[90] Grassberger P. "Toward a Quantitative Theory of Self-Generated Complexity". Int. J. Theor. Phys. 25:907-938, 1986.
[91] Koppel H, Atlan H. "Program-length Complexity, Sophistication and Induction". Inform. Sci., 56:186-213, 1991.
[92] Huberman, B. A. & T. Hogg. "Complexity and Adaptation". Physica D. 22:376-384, 1986.
[92] Kasper, F. & H. G. Schuster. "Easily Calculable Measure for the Complexity of Spatiotemporal Patterns". Phy. Rev. A, 36(2):842-848, 1987.
[94] 刘式达，刘式适．《非线性动力学和复杂现象》，气象出版社，1989．
[95] Wackerbauer, R., et al. A Comparative Classification of Complexity Measures. Chaos, Solitons & Fractals, 4(1): 133-173, 1994.
[96] Atmanspacher, H. et al. "Complexity and Meaning in Nonlinear DynamicaI Systems". Open Systems & Information dynamic, 1:269-289, 1991.
[97] Wackerbauer, R., et al. "A Comparative Classification of Complexity Measures". Chaos, Solitons & Fractals, 4(1): 133-173, 1994.
[98] 孟庆生．《信息论》，西安交通大学出版社，1986．
[99] 金振玉．《信息论》，北京理工大学出版社，1991．
[100] Vastano J A and Swinney H L. "Information Transport in Spatiotemporal Systems[J]". Phys Rev Lett, 1988, 60(18):1773-1776
[101] 王晓萍，黄轶轮．“气固流化床多传感器信息传输的复杂性研究”．《高校化学工程学报》10：585-590，2003．
[102] 黄轶伦，汪乐宇，郑燕萍等．“气固流化床中信息熵的实验研究”．《高校化学工程学报》15(20)：167-173，2002．
[103] 徐京华，童勤业，刘仁．“大脑皮层信息传输和精神分裂症”．《生物物理学报》12(1)：103-108，1996．
[104] 甄玲．《气固流化床信息传输特性及其应用研究》浙江大学硕士论文，2002．
[105] 王晓萍，黄轶轮．“气固流化床信息传输和流型识别”．《化工学报》8：1059-1064，2003．
[106] 蔡希尧．“多源信息融合”．《电子科学技术评论》．1990，(3)．
[107] 康耀红，蔡希尧等．“多传感器数据融合现状综述”．《电子科技大学学报》．计算机专辑，1994．
[108] 周章玉，石福炎．“由压力波动判断气—固流化床中的流化类型”．《化学反心工程与工艺》．15(3)：262-267,1999．
[109] 彭黎辉，张宝芬等．“基于模糊神经元网络的两相流流型辨识方法”．《模式识别与人工智能》．10(4)：332-337，1997．
[110] 赵贵兵等．“散式流态化到聚式流态化的混沌识别”．《化工学报》51(4)：468-479,2000．
[111] J Linas. "A Surrvey of Techniques for CIS Data Fusion". SAIC.ProcVIEE C~3I Conf Bournemouth.
[112] 美国国防部关键技术计划(1992年)。北京：国防科技信息中心，1993．
[113] 郁文贤、雍少为等．“多传感器信息融合技术述评”《国防科技大学学报》16(3)：1-11，1994．
[114] Edward Waltz,James Llians.《多传感器数据融合》赵宗贵等译，电子部28所．
[115] A R June. "A Framework for Automatede Tactical Data Fusion". Fournal of Robotic Systems 7(3):337～372, 1990.
[116] 冀海峰，黄志尧等．“基于信息融合技术的气固流化床流型辨识”．《仪器仪表学报》增刊，23(3)：897-899，2002．
[117] D C A Thomopoulos. "Sensor Integration and Data Fusion". Journal of Robotic Systems 7(3):337～372, 1990.
[118] Pemberton W, et al. "A context dependent automatic target recognize system". Proc.SPIE. Vol,485,May 1984.
[119] P S Charvez. "Digital Merging of Landsat TM and. Digitized NHAP Data for 1:2400 Scale Image Mapping". PERS, 52 (10) 1637-1645, 1986.
[120] Bar-Shalom. "Multitarget—Multisensor Tracking: Adacanced Application". 1987.
[121] Ted J Broida.Performanee "Prediction for Multi-sensor Tracking Systems: Kinematic Accurcay and data Performance". SPIE Vol. 1198.Sensor Fusion Ⅱ, 156-169, 1989.
[122] S S Blackman. "Multiple-target Tracking with Redar Applications". Artech House, Norwood, Masachustts, 1986.
[123] R Johnson. "Automatic Target Recognition Fuse Sensors and Artificial Intelligence". Defense Electronics, 1:106～115, 1984.
[124] R C Luo,et al. "A hierarchical Target Representation for Autonomous Recognition Using Distributed Sensors". Proc. SPIE Conf On Sensor Fusion Ⅲ, 537, 1989.
[125] E Walt. Data "Fusion for C3I Systems". C31 Handbook, EW communication, Palo Altom, Calfornia, 24-29, 1986.
[126] S C A Thomopoulos, et al. "Optimal Decision Distributed Decision Fusion. IEEE Trans". On Aerospace and Electronic Systems, 25(6), 1989.
[127] M A A bidi. "Sensor Fusion: a New Approach and Its Approach and Its Application". In Proc SPIE Conf On sensor Fusion Ⅱ. 235-346, 1989.
[128] H F Durrant-Whyte. "Consistent Integration and Propagation of Disparate Sensor Observation". Inter Journal of Robotics Research, No. 6(3):3～24, 1987.
[129] T P Garey, et al. "An Inference Technique for Integration Knowledge from Disparate Source". Proc the Inter. Joint Conf on Artificial Intelligence, Vancouver, August 319～325, 1981.
[130] E L Waltz, D M Buede. "Data Fusion and Decision Support for Command and control". IEEE Trans. On SMC, 616:865～879, 1986.
[131] Lang hong, et.al. "Recursive Temporal-Spatial Information Fusion with Applications to Target
Identification". IEEE Trans. On Aerospace and Electronic Systems, 29(2):435～445, 1993.
[132] S C A Thomopoulos. "Sensor Integration and Data Fusion". J Robstic Syst. 7(3):337-372 1990.
[133] 李安贵等．《模糊数学及其应用》北京科技大学出版社．1994．
[134] T L Huntsherger, et al. "A Framework for Multisensor Fusion in the Presence of Uncertainty". Proc. Of Workship on Spatial Reasoning and Multi-sensro Fusion, St. Charles, I Ⅲ I, Oct. 345-350, 1987.
[135] S K Rogers. Et.al. "Artificial Neutral Netwrok Technology for Automatuic Target Recognition". SPIE InstituteSeries Vol. IS 7, 231～247, 1990.
[136] 张兆礼等．“无损检测中的基于模糊神经网络数据融合技术”．《电子测量与仪器学报》 15(1)：58-62,2001
[137] 张立明．《人工神经网络的模型及其应用》复旦大学出版社．1993．
[138] 黄串福等．《模糊信息优化处理技术及其应用》 北京航空航天大学出版社．1995．
[139] 汪培庄．《模糊集合论及其应用》上海科学技术出版社 1983．
[140] Zadeh. L. A, Fuzzy sets[J], Information and Control,1965(8),338～35.
[141] 康耀红．《数据融合理论与应用》 西安电子科技大学出版社．1997．
[142] 有本卓著．杨逢春译．近代信息论．北京：人民邮电出版社，1985
[143] 孙涛、张宏建等，基于模糊逻辑融合算法的气液两相流流型辨识方法，仪器仪表学报，2001．6，22(3)：P293-294。
[144] Coifman R R. Wickerhauser M V. "Entropy—Based Algorithms for Best Basis Selection". IEEE Transactions on Information Theory, 1992.38(2):713-718.
[145] 王晓萍等．“多传感器数据融合在气固流化床流型识别中的应用”《化工学报》，待发表。
[146] 孙尚拱等．《实用判别分析》科学出版社．1990．
[147] E Waltz. J Linas. Multisensor Data Fusion, Arrech House. MA. 1990.
[148] 王晓东等．“模糊模式识别在流型判别中的应用”．《油气储运》 18(5)：15-18，1999．
[149] 陈国华．“模糊理论在焊缝缺陷质量等级评定中的应用研究”《无损检测》20(2)：39-41，1998．