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Oscillation Detection and Diagnosis in Process Industries by Pattern Recognition Technique

IFAC-PapersOnLine 2019年第1期52卷 299-304页

作者： Jônathan W.V. Dambros Marcelo Farenzena Jorge O. Trierweiler Group of Intensification Modeling Simulation Control and Optimization of Processes (GIMSCOP) Chemical Engineering Department Federal University of Rio Grande do Sul (UFRGS) R. Eng. Luiz Englert s/n Campus Central Porto Alegre RS Brazil Department of Computer Science University of Kaiserslautern 67663 Kaiserslautern Deutschland

Oscillation in control loops is a frequent problem faced in process industries. It deviates the process variables from their desired condition, affecting negatively plant productivity. To guarantee profitability, oscillation must be detected, diagnosed, and, finally, eliminated. Dozens of automatic detection and diagnosis techniques have been proposed over the last years. However, the application to real industrial data reveals low efficiencies, which indicates that the techniques require improvement. This work presents a new method for oscillation detection and diagnosis. The technique classifies the loops based on the shape of the PV(OP) diagram by a pattern recognition approach, where the model is trained with simulated examples that cover a large range of processes and different conditions found in industrial data, such as noise and disturbance presence. The performance of the proposed technique is compared to well-established oscillation detection and diagnosis methods, returning better results.

关键词： Oscillation detection diagnosis process control fault detection diagnosis pattern recognition process monitoring

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PDG Pressure Estimation in Offshore Oil Well: Extended Kalman Filter vs. Artificial Neural Networks

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IFAC-PapersOnLine 2019年第1期52卷 508-513页

作者： Andressa Apio Jônathan W.V. Dambros Fabio C. Diehl Marcelo Farenzena Jorge O. Trierweiler Group of Intensification Modeling Simulation Control and Optimization of Processes (GIMSCOP) Chemical Engineering Department Federal University of Rio Grande do Sul (UFRGS) R. Eng Luiz Englert s/n Campus Central Porto Alegre RS Brazil Department of Computer Science University of Kaiserslautern 67663 Kaiserslautern Deutschland Research and Development Center Petrobras 21941915 Rio de Janeiro Brazil

The Permanent Downhole Gauge (PDG) pressure measurement is of great importance for offshore oil well modeling and control since it is measured close to the bottom hole. The PDG is installed in a remote undersea environment, which makes expensive the maintenance in case of fault. For this reason, PDG measurements are frequently unavailable. To overcome this limitation, the PDG pressure can be estimated using other available measurements. The estimation is not a simple task since, depending on process operational conditions, the multiphase flow might present limit cycles. In this work, Artificial Neural Network (ANN) and Extended Kalman Filter (EKF) are proposed as potential techniques for the PDG pressure estimation. The comparison of the results shows that ANN returns precise estimation for a short-time window after the failure, but fails when a different process operating condition is applied, while EKF returns good estimation in all the cases.

关键词： Modelling System Identification Data Analytics Machine Learning Inferential sensing State Estimation Sensor Development

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Author Correction: Perceived match between own and observed models' bodies: influence of face, viewpoints, and body size

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Scientific reports 2020年第1期10卷 17120页

作者： Lize De Coster Pablo Sánchez-Herrero Carlos Aliaga Miguel A Otaduy Jorge López-Moreno Ana Tajadura-Jiménez DEI Interactive Systems Group Department of Computer Science and Engineering Universidad Carlos III de Madrid Avenida de la Universidad 30 28911 Leganés Madrid Spain. lcoster@inf.uc3m.es. Seddi Labs Madrid Spain. Modeling and Virtual Reality Group Department of Computer Science Universidad Rey Juan Carlos Madrid Spain. Multimodal Simulation Lab Department of Computer Science and Architecture Computer Systems and Languages Statistics and Operative Investigation Universidad Rey Juan Carlos Madrid Spain. DEI Interactive Systems Group Department of Computer Science and Engineering Universidad Carlos III de Madrid Avenida de la Universidad 30 28911 Leganés Madrid Spain.

An amendment to this paper has been published and can be accessed via a link at the top of the paper.

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Nonlocal and Gradient Theories of Piezoelectric Nanoplates

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Procedia Engineering 2017年 190卷 178-185页

作者： Jan Sladek Vladimir Sladek Jozef Kasala Ernian Pan Institute of Construction and Architecture Slovak Academy of Sciences 84503 Bratislava Slovakia Faculty of Special Technology Alexander Dubcek University of Trencin 91150 Trencin Slovakia Computer Modeling and Simulation Group Department of Civil Engineering University of Akron Akron OH 44325-3905 USA

Classical continuum models are unable to describe the size effect in nano/micro structures, even though this effect is observed experimentally. Therefore, modified continuum models are frequently applied for the investigation of nanomechanics due to their computational efficiency and capability of providing accurate results which are comparable to the atomistic models. In this paper, the Mindlin plate is extended to the piezoelectric nanoplate with nonlocal and gradient theories for size effect. The governing equations for bending moments, normal and shear stresses are derived via the Hamilton‘s principle. Differences between the two theories are described.

关键词： Nonlocal gradient elasticity Mindlin plate Hamilton‘s principle size effect

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Tracking and Counting Motion for Monitoring Food Intake Based-On Depth Sensor and UDOO Board: A Comprehensive Review

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IOP Conference Series: Materials Science and Engineering 2017年第1期226卷

作者： Muhammad Fuad bin Kassim Mohd Norzali Haji Mohd Embedded Computing Systems (EmbCos) Department of Computer Engineering Faculty of Electrical and Electronic Engineering Universiti Tun Hussein Onn Malaysia 86400 Parit Raja Batu Pahat Johor Malaysia Modeling and Simulation (BIOMEMS) Research Group Department of Electronic Engineering Faculty of Electrical and Electronic Engineering Universiti Tun Hussein Onn Malaysia 86400 Parit Raja Batu Pahat Johor Malaysia

Technology is all about helping people, which created a new opportunity to take serious action in managing their health care. Moreover, Obesity continues to be a serious public health concern in the Malaysia and continuing to rise. Obesity has been a serious health concern among people. Nearly half of Malaysian people overweight. Most of dietary approach is not tracking and detecting the right calorie intake for weight loss, but currently used tools such as food diaries require users to manually record and track the food calories, making them difficult for daily use. We will be developing a new tool that counts the food intake bite by monitoring hand gesture and face jaw motion movement of caloric intake. The Bite count method showed a good significant that can lead to a successful weight loss by simply monitoring the bite taken during eating. The device used was Kinect Xbox One which used a depth camera to detect the motion on person hand and face during food intake. Previous studies showed that most of the method used to count bite device is worn type. The recent trend is now going towards non-wearable devices due to the difficulty when wearing devices and it has high false alarm ratio. The proposed system gets data from the Kinect that will be monitoring the hand and face gesture of the user while eating. Then, the gesture of hand and face data is sent to the microcontroller board to recognize and start counting bite taken by the user. The system recognizes the patterns of bite taken from user by following the algorithm of basic eating type either using hand or chopstick. This system can help people who are trying to follow a proper way to reduce overweight or eating disorders by monitoring their meal intake and controlling eating rate.

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Model checking CSL for markov population models 12

Model checking CSL for markov population models

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12th International Workshop on Quantitative Aspects of Programming Languages and Systems, QAPL 2014

作者： Spieler, David Hahn, Ernst Moritz Zhang, Lijun Modeling and Simulation Group Computer Science Department Saarland University Saarbrücken Germany State Key Laboratory of Computer Science Institute of Software Chinese Academy of Sciences Beijing China

Markov population models (MPMs) are a widely used modelling formalism in the area of computational biology and related areas. The semantics of a MPM is an infinite-state continuous-time Markov chain. In this paper, we use the established continuous stochastic logic (CSL) to express properties of Markov population models. This allows us to express important measures of biological systems, such as probabilistic reachability, survivability, oscillations, switching times between attractor regions, and various others. Because of the infinite state space, available analysis techniques only apply to a very restricted subset of CSL properties. We present a full algorithm for model checking CSL for MPMs, and provide experimental evidence showing that our method is effective. © 2014 D. Spieler, E. M. Hahn & L. Zhang.

关键词： Model checking

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Fracture analysis in piezoelectric semiconductors under a thermal load 3rd

Fracture analysis in piezoelectric semiconductors under a th...

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International Conference on Computational Methods for Thermal Problems, ThermaComp 2014

作者： Sladek, Jan Sladek, Vladimir Pan, Ernian Wünsche, Michael Institute of Construction and Architecture Slovak Academy of Sciences Bratislava84503 Slovakia Computer Modeling and Simulation Group Department of Civil Engineering University of Akron AkronOH44325-3905 United States Department of Civil Engineering University of Siegen SiegenD-57068 Germany

ISBN: (纸本)9788874317271

This paper presents in-plane crack problem in piezoelectric semiconductors under a transient thermal load. General boundary conditions and sample geometry are allowed in the proposed formulation. The governing partial differential equations for stresses, electric displacement field and current are satisfied in a local weak-form on small fictitious subdomains. All field quantities are approximated by the moving least-squares (MLS) scheme. After performing the spatial integrations, one obtains a system of ordinary differential equations for certain nodal unknowns. The influence of initial electron density on the intensity factors and energy release rate is investigated.

关键词： Heat conduction

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26th Annual Computational Neuroscience Meeting (CNS*2017) of the Organization for Computational Neuroscience Antwerp, Belgium, July 15-20, 2017

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BMC NEUROSCIENCE 2017年第SUPPL 1期18卷 59-59页

作者： [Anonymous] Indiana University Purdue University Indianapolis Indianapolis IN 46032 USA Stark Neurosciences Research Institute Indiana University School of Medicine Indianapolis IN 46032 USA Department of Mathematics East Carolina University Greenville NC 27858 USA Jülich Supercomputing Centre Forschungszentrum Jülich 52425 Jülich Germany Future Systems Swiss National Supercomputing Centre 8092 Zurich Switzerland User Engagement and Support Swiss National Supercomputing Centre 6900 Lugano Switzerland Institut de Neurosciences des Systèmes Aix Marseille Univ 13005 Marseille France Simulation Lab Neuroscience Forschungszentrum Jülich Jülich Germany Department of Experimental Psychology Ghent University 9000 Ghent Belgium Donders Center for Cognitive Neuroimaging Radboud University 6525HR Nijmegen The Netherlands Department of Electrical Computer and Energy Engineering University of Colorado Boulder CO 80309 USA Department of Neurosurgery Johns Hopkins School of Medicine Baltimore MD 21287 USA Department of Neurology Johns Hopkins School of Medicine Baltimore MD 21287 USA Department of Otolaryngology Johns Hopkins School of Medicine Baltimore MD 21287 USA INSERM U968 Paris France Sorbonne Universités UPMC University Paris 06 UMR_S 968 Institut de la Vision Paris France CNRS UMR_7210 Paris France Department of Computer Architecture and Technology University of Granada (CITIC) Granada Spain Sorbonne Universités UPMC Univ Paris 06 INSERM CNRS Institut de la Vision Paris France Department of Adaptive Machine Systems Osaka University Osaka Japan Department of Computer Science University of Cergy-Pontoise Cergy-Pontoise France Department of Physics and Astronomy College of Charleston Charleston SC 29424 USA School of Physics Faculty of Science University of Sydney Sydney NSW 2006 Australia Center of Excellence for Integrative Brain Function Australian Research Council Sydney Australia Max Planck Institute for Human Cognitive and Brain Sciences Saxony Lei

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26th Annual Computational Neuroscience Meeting (CNS*2017): Part 3 Antwerp, Belgium. 15-20 July 2017 Abstracts

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BMC NEUROSCIENCE 2017年第SUPPL 1期18卷 95-176页

作者： [Anonymous] Department of Neuroscience Yale University New Haven CT 06520 USA Department Physiology & Pharmacology SUNY Downstate Brooklyn NY 11203 USA NYU School of Engineering 6 MetroTech Center Brooklyn NY 11201 USA Departament de Matemàtica Aplicada Universitat Politècnica de Catalunya Barcelona 08028 Spain Institut de Neurobiologie de la Méditerrannée (INMED) INSERM UMR901 Aix-Marseille Univ Marseille France Center of Neural Science New York University New York NY USA Aix-Marseille Univ INSERM INS Inst Neurosci Syst Marseille France Laboratoire de Physique Théorique et Modélisation CNRS UMR 8089 Université de Cergy-Pontoise 95300 Cergy-Pontoise Cedex France Department of Mathematics and Computer Science ENSAT Abdelmalek Essaadi’s University Tangier Morocco Laboratory of Natural Computation Department of Information and Electrical Engineering and Applied Mathematics University of Salerno 84084 Fisciano SA Italy Department of Medicine University of Salerno 84083 Lancusi SA Italy Dipartimento di Fisica Università degli Studi Aldo Moro Bari and INFN Sezione Di Bari Italy Data Analysis Department Ghent University Ghent Belgium Coma Science Group University of Liège Liège Belgium Cruces Hospital and Ikerbasque Research Center Bilbao Spain BIOtech Department of Industrial Engineering University of Trento and IRCS-PAT FBK 38010 Trento Italy Department of Data Analysis Ghent University Ghent 9000 Belgium The Wellcome Trust Centre for Neuroimaging University College London London WC1N 3BG UK Department of Electronic Engineering NED University of Engineering and Technology Karachi Pakistan Blue Brain Project École Polytechnique Fédérale de Lausanne Lausanne Switzerland Departement of Mathematics Swansea University Swansea Wales UK Laboratory for Topology and Neuroscience at the Brain Mind Institute École polytechnique fédérale de Lausanne Lausanne Switzerland Institute of Mathematics University of Aberdeen Aberdeen Scotland UK Department of Integrativ

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TRANSIENT RESPONSE OF A BI-LAYERED MULTIFERROIC COMPOSITE PLATE

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Acta Mechanica Solida Sinica 2011年第1期24卷 83-91页

作者： Ruifeng Wang Qingkai Han Ernian Pan Computer Modeling and Simulation Group College of Engineering University of Akron Akron Ohio 44325-3905 USA School of Mechanical Engineering and Automation Northeastern University Shenyang 110004 China

In this paper, a three-dimensional finite-element formulation for the multiferroic composite is developed and implemented into the commercial software ABAQUS for its transient analysis. First, a special three-dimensional eight-node solid element is designed to handle the multiferroic composite made of elastic, piezoelectric, and piezomagnetic materials. Second, a userdefined subroutine for this newly developed element is implemented into ABAQUS. Finally, the transient responses of a bi-layered multiferroic composite are calculated by using the direct time integration method. Two typical magnetic potential signals, Gauss and Ricker pulses, are applied to the composite with various time durations of excitation. The induced electric field shows that the transient response can be substantially influenced by the input signal, which could be tuned for the strongest electric output.

关键词： transient response multiferroic piezoelectric piezomagnetic composite finite element

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