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Application of nonlinear PCA for fault detection in polymer extrusion processes

NEURAL COMPUTING & APPLICATIONS 2012年第6期21卷 1141-1148页

作者： Liu, Xueqin Li, Kang McAfee, Marion Deng, Jing Queens Univ Belfast Sch Elect Elect Engn & Comp Sci Belfast BT9 5AH Antrim North Ireland Inst Technol Sligo Dept Mech & Elect Engn Sligo Ireland

This paper describes the application of an improved nonlinear principal component analysis (PCA) to the detection of faults in polymer extrusion processes. Since the processes are complex in nature and nonlinear relationships exist between the recorded variables, an improved nonlinear PCA, which incorporates the radial basis function (RBF) networks and principal curves, is proposed. This algorithm comprises two stages. The first stage involves the use of the serial principal curve to obtain the nonlinear scores and approximated data. The second stage is to construct two RBF networks using a fast recursive algorithm to solve the topology problem in traditional nonlinear PCA. The benefits of this improvement are demonstrated in the practical application to a polymer extrusion process.

关键词： Nonlinear principal component analysis Polymer extrusion process RBF networks fast recursive algorithm

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APPROXIMATION OF MULTIVARIABLE LINEAR-SYSTEMS WITH IMPULSE-RESPONSE AND AUTO-CORRELATION SEQUENCES

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AUTOMATICA 1983年第3期19卷 265-277页

作者： INOUYE, Y Department of Control Engineering Faculty of Engineering Science Osaka University Toyonaka Osaka 60 Japan

This paper considers the construction of approximants of multi-input-multi-output, discrete-time linear systems from the finite data of the impulse response and autocorrelation sequences. In the approximation of a multivariable linear system, it is common practice to use a finite portion of its impulse response sequence. This is formally equivalent to the Padé approximation technique, which may produce unstable approximants, even though the original system is stable. Mullis and Roberts proposed a new method, which yields stable approximants, in connection with approximation of digital filters. This is, however, restricted to the single-input-single-output case. This paper extends their method to the multi-input-multi-output case and shows a fast recursive algorithm to construct stable approximants of linear systems.

关键词： correlation method fast recursive algorithm interpolation problem least-squares approximation Modelling multivariable systems sampled data systems

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A high-efficiency digital image correlation method based on a fast recursive scheme

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MEASUREMENT SCIENCE AND TECHNOLOGY 2010年第3期21卷 035101-035101页

作者： Huang, Jianyong Zhu, Tao Pan, Xiaochang Qin, Lei Peng, Xiaoling Xiong, Chunyang Fang, Jing Peking Univ Dept Biomed Engn Beijing 100871 Peoples R China Peking Univ Acad Adv Interdisciplinary Studies Beijing 100871 Peoples R China Peking Univ Third Hosp Inst Vasc Med Beijing 100083 Peoples R China

Due to computational complexity of correlation searching, the digital image correlation (DIC) method is often extremely time consuming in image processing and optical measurement, which has limited its further applications to a great extent. This paper develops a fast recursive scheme to mathematically reduce the computational burden of the traditional DIC technique and therefore improve its efficiency in deformation calculation. A global sum-table approach is proposed to simplify the computations of all double sums arising in the zero-normalized cross-correlation coefficient (ZNCC). A fast recursive algorithm is established to accelerate the calculation of the cross-correlation term in the ZNCC. Both theoretical analysis and actual displacement acquisition are carried out to validate the performance of the new DIC algorithm, which indicates that the fast recursive scheme can improve computational efficiency of integer-pixel correlation searching by about 10 to 50 times in comparison with the classic DIC algorithm, on the condition of keeping the measurement accuracy.

关键词： zero-normalized cross correlation sum tables fast recursive algorithm cell-substrate displacement measurement

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Control of Organic Rankine Cycle for Waste Heat Recovery Based on An Optimized Predictive Model 36

Control of Organic Rankine Cycle for Waste Heat Recovery Bas...

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第36届中国控制会议

作者： Kailong Liu Kang Li Mingming Lin Jianhua Zhang Queen's University Belfast Qingdao University of Science and Technology North China Electric Power University

ISBN: (纸本)9781538629185

The Organic Rankine Cycle(ORC) is a promising technique to recover low grade waste heat,and thus helps to improve the overall thermal efficiency of a process and reduce the environmental impact of large consumption of fossil fuels.A proper control strategy is a key for the safe and efficient operation of the ORC *** this paper,the key components in the ORC system are introduced *** a constrained generalized predictive control(CGPC) is designed to control the process.A controlled auto-regressive integrated moving average(CARIMA) model is used as the online self-tuning predictive model for the GPC controller,while the structure of the CARIMA model is optimized by the fast recursive algorithm(FRA).Simulation results confirm that the developed ORC control strategy is capable of achieving desirable set-point tracking performance,while also has a satisfactory disturbance rejection capability.

关键词： Organic Rankine Cycle Waste heat recovery Constrained generalized predictive control fast recursive algorithm

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A Novel Hybrid Data-driven Method for Li-ion Battery Internal Temperature Estimation 11

A Novel Hybrid Data-driven Method for Li-ion Battery Interna...

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11th UKACC International Conference on Control (UKACC Control)

作者： Liu, Kailong Li, Kang Deng, Jing Queens Univ Belfast Sch Elect Elect Engn & Comp Sci Belfast BT9 5AH Antrim North Ireland

ISBN: (纸本)9781467398916

Accurate battery internal temperature estimation is a key for safe battery operation of electric vehicles. In this paper, a novel hybrid data-driven method combining a linear neural network (NN) model and an extended Kalman filter (EKF) is developed to estimate the internal temperature of a LiFePo4 battery. In order to select the proper input terms of the linear NN model and estimate the associated parameters, a fast recursive algorithm (FRA) is firstly used. Then an EKF with a battery lumped thermal model as the state function is used to filter out the outliers and reduce the errors in estimating the internal temperature based on the linear NN model. The test results from two different experiment data demonstrate that the hybrid method can achieve good estimation accuracy, and the method can be easily applied to other type of batteries.

关键词： Battery internal temperature estimation Linear neural network fast recursive algorithm Extended Kalman filter Lumped thermal model

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Structure-adaptive image filtering using trimmed mean filters 8

Structure-adaptive image filtering using trimmed mean filter...

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Conference on Nonlinear Image Processing VIII

作者： Palenichka, RM Zinterhof, P National Academy of Sciences of Ukraine (Ukraine) Univ. Salzburg (Austria)

ISBN: (纸本)0819424374

In this paper, a structure-adaptive approach to the nonlinear image filtering is described. The adaptive procedure is based on selection of the most homogenous neighborhood region from several possible structuring regions by the principle of maximum a posteriori probability. Then, an optimal evaluation of the pixel value is performed involving pixels from the determined neighborhood region. Trimmed mean filters are used for the robust evaluation of local properties during estimation of object and background intensities when the noise has a mixed conditional distribution, e.g. normal distribution with outliers.

关键词： structure-adaptive filtering trimmed mean mathematical morphology structuring element structuring region fast recursive algorithm

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Approximation of Multivariable Linear Systems with Impulse Response and Autocorrelatlon Sequences

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IFAC Proceedings Volumes 1981年第2期14卷 1-6页

作者： Y. Inouye Department of Control Engineering Faculty of Engineering Science Osaka University Toyonaka Osaka 560 japa

This paper considers the construction of approximants of multi-input-output, discrete-time linear systems from the finite data of the impluse response and autocorrelation sequences (or cross correlation between input and output, and autocorrelation of output). In the approximation of multivariable linear systems, it is common practice to use the impluse response sequence This is formally equivalent to the Padé approximation technique, which may produce unstable approximants, even though the original system is stable. Mullis and Roberts proposed a new method, which yields stable appr0ximants, in connection with the approximation of digital filters. This is, however, restricted to the single input-output case. This paper extends their method to the multi-input-output case and shows a fast recursive algorithm to construct stable approximants of linear systems

关键词： Modelling multivariable systems correlation methods least squares approximation interpolation problem sampled data systems fast recursive algorithm

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An Effective Method of Threshold Selection for Small Object Image

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Defence Technology（防务技术） 2011年第4期7卷 235-242页

作者：吴一全吴加明占必超 School of Electronic and Information Engineering Nanjing University of Aeronautics and Astronautics Science and Technology on Electro-optic Control Laboratory Institute of Electro-optic Equipment of AVIC State Key Laboratory of Novel Software Technology Nanjing University

The image segmentation difficulties of small objects which are much smaller than their background often occur in target detection and recognition. The existing threshold segmentation methods almost fail under the circumstances. Thus, a threshold selection method is proposed on the basis of area difference between background and object and intra-class variance. The threshold selection formulae based on one-dimensional (1-D) histogram, two-dimensional (2-D) histogram vertical segmentation and 2-D histogram oblique segmentation are given. A fast recursive algorithm of threshold selection in 2-D histogram oblique segmentation is derived. The segmented images and processing time of the proposed method are given in experiments. It is compared with some fast algorithms, such as Otsu, maximum entropy and Fisher threshold selection methods. The experimental results show that the proposed method can effectively segment the small object images and has better anti-noise property.

关键词： information processing small infrared target detection image segmentation threshold selection 2-D histogram oblique segmentation fast recursive algorithm

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High Gain Converter with Improved Radial Basis Function Network for Fuel Cell Integrated Electric Vehicles

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WORLD ELECTRIC VEHICLE JOURNAL 2022年第2期13卷 31页

作者： Girirajan, Balasubramanian Shekhar, Himanshu Lai, Wen-Cheng Jagannathan, Hariraj Kumar Divakarachar, Parameshachari Bidare SR Univ Collaboratory Social Innovat Warangal 506371 Andhra Pradesh India Hindustan Inst Technol & Sci Dept Elect & Commun Engn Kelambakkam 603103 India Natl Yunlin Univ Sci & Technol Dept Elect Engn Touliu Yunlin 64002 Taiwan Sona Coll Technol Dept Elect & Commun Engn Salem 636005 India GSSS Inst Engn & Technol Women Dept Telecommun Engn Mysuru 570016 India

In a recent trend, electric vehicles (EV) have been facing various power quality issues, so fuel cells (FC) are considered the best choice for integrating EV technology to enhance performance. A fuel cell electric vehicle (FCEV) is a type of EV that uses a fuel cell combined with a small battery or super-capacitor to power its on-board electric motor. However, the power obtained from the FC system is much less and is not enough to drive the EV. So, another energy source is required to deliver the demanded power, which should contain high voltage gain with high conversion efficiency. The traditional converter produces a high output voltage at a high duty cycle, which generates various problems, such as reverse recovery issues, voltage spikes, and less lifespan. High switching frequency and voltage gain are essential for the propulsion of FC-based EV. Therefore, this paper presents an improved radial basis function (RBF)-based high-gain converter (HGC) to enhance the voltage gain and conversion efficiency of the entire system. The RBF neural model was constructed using the fast recursive algorithm (FRA) strategy to prune redundant hidden-layer neurons. The improved RBF technique reduces the input current ripple and voltage stress on the power semiconductor devices to increase the conversion ratio of the HGC without changing the duty cycle value. In the end, the improved RBF with HGC achieved an efficiency of 98.272%, vehicle speed of 91 km/h, and total harmonic distortion (THD) of 3.12%, which was simulated using MATLAB, and its waveforms for steady-state operation were analyzed and compared with existing methods.

关键词： electric vehicle fast recursive algorithm fuel cell high-gain converter improved radial basis function network

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Image segmentation based on the maximum between-cluster average deviation of the 2D bound histogram

Image segmentation based on the maximum between-cluster aver...

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2012 International Conference on Computer Technology and Science(ICCTS 2012)

作者： Yong-liang Jin,Yan-jie Wang Changchun Institute of Optics,Fine Mechanics and Physics,Chinese Academy of Sciences

In order to further improve the accuracy and real-time performance of image segmentation,a new method for image segmentation,which combines the virtues of 2D bound histogram and maximum between-cluster average deviation,is ***,construct the bound set and limit the histogram to region of interest for purpose of reducing the interference of background and *** then,the optimal segmenting threshold is obtained by searching in the region of interest for image segmentation using the maximum between-cluster average ***,the fast recurring algorithm,which is brought forward by the reference,is improved for accelerating the running speed of the *** types of infrared images are selected to compare the results of purposed algorithm and the algorithms in *** show that the proposed algorithm has better segmentation effect,higher segmentation accuracy,less segmentation failure and the running speed is enhanced by more than thirty *** bound histogram can be constructed aiming at concrete problem,based on prior knowledge,so it has better generality.

关键词： 2D bound histogram Image segmentation Maximum between-cluster average deviation fast recursive algorithm

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