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International Conference on Computer and information Technology (CIT)

作者： Feng Xuewei Wang Dongxia Zeng Jiemei Ma Guoqing Li Jin National Key Laboratory of Science and Technology on Information System Security Beijing Institute Beijing China Beijing Aerospace Control Center Beijing China

It is unfeasible to analyze the security events by the manual way for the security manager, because the number of the events is huge and the information contained in the events is meaningless. After analyzing the existing algorithms of security events correlation, we propose an attack scenario reconstruction technology based on state machine. The processes of attackers intruding into the cyberspace can be restored and the more comprehensive attack scenario description information will be generated using this technology. This working lets the security manager more comfy. The state machine based attack scenario reconstruction technology processes security events using clustering analysis and causal analysis concurrently, it builds a correlation state machine in memory for every attack scenario tree which is predefined by the security manager, when security events are coming, the certain state machines will process them, if the condition is satisfied, an attack scenario description information will be generated and then sent to the security manager. The correlating technology based on state machine is more timely and accurately, and at last, we use the DARPA2000 Intrusion Scenario Specific Data Sets to validate the technology, the experiment results show that it is feasible to analyze security events using the technology we proposed.

关键词： Correlation Cyberspace Computer crime Engines XML Protocols

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Soft sensor modeling of ball mill load via principal component analysis and support vector machines

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7th International Symposium on Neural Networks, ISNN 2010

作者： Tang, Jian Zhao, Lijie Yu, Wen Yue, Heng Chai, Tianyou Key Laboratory of Integrated Automation of Process Industry Ministry of Education Northeastern University Shenyang 110819 China College of Information Engineering Shenyang Institute of Chemical Technology Shenyang 110142 China Departamento de Control Automatico CINVESTAV-IPN Av.IPN 2508 México D.F. 07360 Mexico

ISBN: (纸本)9783642129896

In wet ball mill, measurement accuracy of mill load (ML) is very important. It affects production capacity and energy efficiency. A soft sensor method is proposed to estimate the mill load in this paper. Vibration signal of mill shell in time domain is first transformed into power spectral density (PSD) using fast Fourier transform (FFT), such that the relative amplitudes of different frequencies contain mill load information directly. Feature variables at low, medium and high frequency bands are extracted through principal component analysis (PCA), which selects input as a preprocessing procedure to improve the modeling performance. Three support vector machine (SVM) models are built to predict the mill operating parameters. A case study shows that proposed soft sensor method has higher accuracy and better predictive performance than the other normal approaches. © 2010 Springer-Verlag Berlin Heidelberg.

关键词： Principal component analysis

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Improving transient response of adaptive control systems using multiple neural network models

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7th International Symposium on Neural Networks, ISNN 2010

作者： Li, Xiao-Li Yu, Xiang Zhang, Yan Department of Automation Information and Engineering School University of Science and Technology Beijing Beijing 100083 China Key Laboratory of Advanced Control of Iron and Steel Process Ministry of Education University of Science and Technology Beijing Beijing 10083 China Graduate School of Education University of Pennsylvania 3451 Walnut Street Philadelphia PA 19104 United States

ISBN: (纸本)9783642129896

Multiple Radial Basis Function (RBF) neural network models are used to approximate a kind of discrete time nonlinear system described by a combination of nonlinear and linear part. Based on these models, Multiple model adaptive control strategy is given to improve the transient response of closed-loop system. Simulations according to different uncertain changing parameters in the model of the system are studied to show the efficiency of the proposed method. © 2010 Springer-Verlag Berlin Heidelberg.

关键词： Transient analysis

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Study of distributed multiaxial intelligent tightening machine based on fieldbus control system

Study of distributed multiaxial intelligent tightening machi...

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International Conference on Intelligent control and information processing (ICICIP)

作者： Yunsheng Fan Chen Guo Wei Meng Department of Traffic Information Engineering and Control Navigation College Dalian Maritime University Dalian China Key Laboratory of Simulation and Control of Navigation System College of Information Science and Technology Dalian Maritime University Dalian China

We put forward a system structure of controlling the tightening operation of bolts using multiraxial tightening machine. A kind of fieldbus intelligent tightening control system is designed with the technology developing of fieldbus intelligent instrumentation. This system is a distributed structure based on fieldbus control system which consists of CAN bus, Profibus-DP bus, and adopts many advanced intelligent control methods. This system structure and intelligent control method study realizes integration of manufacture, control and management in the tightening of bolts and improves the level of network manufacture and information management of automobile industry. The integrating of tightening machine and fieldbus brings a new thought of automobile industry control technology.

关键词： Torque Fasteners Hardware Automobiles Torque measurement Force

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Estimation of component concentrations of sodium aluminate solution via PLS and Hammerstein recurrent neural networks

Estimation of component concentrations of sodium aluminate s...

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International Workshop on Advanced Computational Intelligence (IWACI)

作者： Wei Wang Lijie Zhao Tianyou Chai Wen Yu Key Laboratory of Integrated Automation of Process Industry Ministry of Education Northeastern University China Key Laboratory of Integrated Automation of Process Industry Shenyang Institute of Chemical Technology Information Engineering School Ministry of Education China Key Laboratory of Integrated Automation of Process Industry Ministry of Education and Research Center of Automation Northeastern University China Departamento de Control Automatico CINVESTAV Mexicali Mexico

In this paper, a new on-line soft sensing method is proposed for component concentrations of sodium aluminate solution. With this sensing strategy, real-time control and optimization can be realized in aluminate production plants. Several advance techniques are used, such as PLS (Partial Least Squares), Hammerstein model, recurrent neural networks and least square algorithm. Industrial experiment results show that the proposed soft sensing algorithm is effective.

关键词： Nonlinear dynamical systems Recurrent neural networks Computational modeling Heuristic algorithms Temperature measurement Data models Artificial neural networks

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The bifurcation analysis and chaos anti-control of a differential-algebraic system

The bifurcation analysis and chaos anti-control of a differe...

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International Conference on Bio-Inspired Computing: Theories and Applications, BICTA

作者： Hong Niu Chao Liu Yajun Zhang Haiyi Sun Institute of System Science Key Laboratory of Integrated Automation of Process Industry Ministry of Education Department of Information and Computational Science Northeastern University Shenyang China Northeastern University Qinhuangdao China

In this paper, the nonlinear and linear mathematical model of a Continuous Stirred Tank Reactor (CSTR) where an irreversible exothermic reaction takes place is considered. Then a differential-algebraic system (DAS) is established for such an irreversible exothermic reaction. We analyze the stability and the bifurcation of the differential-algebraic system. Chaos is not only useful but also very desirable in fluid mixing. If the dynamics of the particle motion in the two fluids are strongly chaotic, two fluids can be thoroughly mixed and the consumed energy is minimized. For this reason, an adaptive controller is designed to make the DAS chaotic. Numerical simulations are performed to illustrate the analytical results.

关键词： Biology

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Modelling of mill load for wet ball mill via GA and SVM based on spectral feature

Modelling of mill load for wet ball mill via GA and SVM base...

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2010 IEEE 5th International Conference on Bio-Inspired Computing: Theories and Applications, BIC-TA 2010

作者： Zhao, Lijie Tang, Jian Yu, Wen Yue, Heng Chai, Tianyou College of Information Engineering Shenyang University of Chemical Technology Shenyang I10142 China Key Laboratory of Integrated Automation of Process Industry Northeastern University Ministry of Education Shen yang Liaoning China Departamento de Control Automatico CINVESTAV-IPN Av.IPN 2508 México D.F. 07360 Mexico

ISBN: (纸本)9781424464388

The load of wet ball mill is a key parameter for grinding process, which affects the productivity, quality and energy consumption. A new soft sensor approach based on the mill shell vibration signal is proposed in this paper. As the frequency domain signal contains more evidently information than time domain, the power spectral density (PSD) of the vibration signal was obtained via fast Fourier transform (FFT). And then the mass and the central frequency of the small peaks of the spectrum are extracted as the spectral features. At last the support vector machines (SVM) is used to build the soft model. The parameters of SVM, the input variables including the mass and the central frequency of the peaks are selected by Genetic algorithm (GA). Experimental results show that proposed soft sensor model has higher accuracy and better predictive performance than the other normal approaches. © 2010 IEEE.

关键词： Genetic algorithms

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Internal model control for hysteretic nonlinear systems based on support vector regression

Internal model control for hysteretic nonlinear systems base...

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World Congress on Intelligent control and Automation (WCICA)

作者： Wenguang Zhang Jianqin Mao Yanhua Ma Beijing Key Laboratory of Measurement and Control Technology and System for Industrial Process Control & Computer Engineering School North China Electric Power University Beijing China School of Automation Science and Electrical Engineering Beijing Aeronautics and Astronautics University Beijing China

Aim at the hysteretic nonlinearity characteristic of the giant magnetostrictive actuator in control, an internal model control method based on support vector regression is presented in this paper. Its models are built by support vector regression using the input and output data of the actuator and the internal model control is achieved. The simulation results show the method in this paper has better control precision.

关键词： Support vector machines Actuators Automation Data models Computational modeling Hysteresis Magnetostriction

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A Hierarchical Image Annotation Method Based on SVM and Semi-supervised EM

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自动化学报 2010年第7期36卷 960-967页

作者： GAO Yan-Yu YIN Yi-Xin UOZUMI Takashi School of Information Engineering University of Science and Technology Beijing Beijing 100083 P.R.China Key Laboratory of Advanced Control of Iron and Steel Process (Ministry of Education) University of Science and Technology Beijing Beijing 100083 P. R. China Department of Computer Science and Systems Engineering Muroran Institute of Technology Muroran 050- 8585 Japan

Automatic image annotation, which aims at automatically identifying and then assigning semantic keywords to the meaningful objects in a digital image, is not a very difficult task for human but has been regarded as a difficult and challenging problem to machines. In this paper, we present a hierarchical annotation scheme considering that generally human s visual identification to a scenery object is a rough-to-fine hierarchical process. First, the input image is segmented into multiple regions and each segmented region is roughly labeled with a general keyword using the multi-classification support vector machine. Since the results of rough annotation affect fine annotation directly, we construct the statistical contextual relationship to revise the improper labels and improve the accuracy of rough annotation. To obtain reasonable fine annotation for those roughly classified regions, we propose an active semi-supervised expectation-maximization algorithm, which can not only find the representative pattern of each fine class but also classify the roughly labeled regions into corresponded fine classes. Finally, the contextual relationship is applied again to revise the improper fine labels. To illustrate the effectiveness of the presented approaches, a prototype image annotation system is developed, the preliminary results of which showed that the hierarchical annotation scheme is effective.

关键词：数字图像自动化系统准确性意义图像标注

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Nonperiodic cycle detection and application in gas liquid two-phase flow

Nonperiodic cycle detection and application in gas liquid tw...

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IEEE Instrumentation and Measurement Technology Conference

作者： Yuncheng Du Huaxiang Wang Dongping Du School of Electrical Engineering and Automation Tianjin Key Laboratory of Process Measurement and Control Tianjin University TJU China School of Mechanical Electronic and Information Engineering China University of Mining and Technology Beijing China

ISBN: (纸本)9781424428328;9781424428335

Nonperiodic cycle detection methods for gas/liquid two phase flow system were discussed. Cycle detection methods, such as Hurst analysis, the V statistic and the P statistic were briefly reviewed; in addition, a modified P statistic method was introduced. Two types of time series, i.e. mathematically sine wave time series and experimental electrical capacitance tomography time series of plug flow and slug flow under different flow conditions were investigated to verify the effectiveness of different cycle detection methods. The sine wave time series and sine wave time series under gauss noise were used to validate different cycle detection methods. For the electrical capacitance tomography time series of different flow regime, discrete wavelet transform (DWT) was adopted to decompose the original signal into approximate signal and detail signals, and then different cycle detection methods were mainly applied to realize cyclic characterization analysis of detail signals for plug flow and slug flow. The results show that the nonperiodic cycle characteristic analysis can reflect the property of different flow regimes.

关键词： Fluid flow Statistical analysis Discrete wavelet transforms Electrical capacitance tomography Plugs Phase detection Gaussian noise Wavelet analysis Signal analysis Time series analysis

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