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Clemson University Power Systems Conference (PSC)

作者： Vitor N. Coelho Frederico G. Guimarães Agnaldo J. R. Reis Bruno N. Coelho Igor M. Coelho Marcone J. F. Souza Departament of Electrical Engineering Federal University of Minas Gerais Belo Horizonte Brazil Department of Control and Automation Engineering Federal University of Ouro Preto MG Brazil Institute of Computing Fluminense Federal University Niterói Brazil Department of Computer Science Federal University of Ouro Preto MG Brazil

Energy plants represent large energy consumers with a wide array of energy needs, assets (e.g. boilers, chillers, storage, on-site generation), and constraints on operations. An innovative energy management system for energy plants is presented in this paper. Through predictive optimization of plant assets, energy analytics, pricing signals, and historical and realtime data, the online energy management system supplies energy plants with salient hourly, real-time recommendations and enables “what-if” analysis to achieve improved economic efficiency. Within a systems context, the paper draws upon ideas from power systems and highlights technical issues related to plant optimization. The paper also describes actual implementations of the energy management solution at two energy plants in the US, providing economic details and an analysis of the savings achieved.

关键词： Turbines Natural gas Boilers Cooling Economics Optimization

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Modelling and validation of a regenerative shock absorber system

Modelling and validation of a regenerative shock absorber sy...

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International Conference on automation and computing (ICAC)

作者： Ruichen Wang Zhi Chen Haijun Xu Karsten Schmidt Fengshou Gu Andrew.D. Ball Centre for Efficiency and Performance Engineering University of Huddersfield Huddersfield UK Department of Vehicle Engineering Taiyuan University of Technology Taiyuan Shanxi P.R. China School of Mechatronics and Automation National University of Defense Technology Changsha Hunan P.R. China Department of Computing and Engineering Frankfurt University of Applied Sciences Frankfurt Germany

For effective energy regeneration and vibration dampening, energy regenerative suspension systems have received more studies recently. This paper presents the dynamic modeling and a test system of a regenerative shock absorber system which converts vibration motion into rotary motion through the adjustment of hydraulic flow. Hydraulic circuit configuration achieves the one way flow and energy regeneration during both compression and extension strokes. The dynamic modeling is performed for the evaluation of design concept and the feasibility studies of regenerative shock absorber system theoretically. Based on simulated results, the efficiency of hydraulic transmission is optimized and validated in test system. The results show that the performance of hydraulic fluid, the features of rotary motion and the capability of energy regeneration are verified and compared between dynamic modeling and experiments. Meanwhile, the average power of 118.2W and 201.7W with the total energy conversion of 26.86% and 18.49% can be obtained based on experiments under sinusoidal inputs with 0.07854m/s and 0.1256m/s respectively.

关键词： Shock absorbers DC motors Valves Shafts Generators Permanent magnet motors Voltage measurement

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Security impact assessment of industrial automation systems using genetic algorithm and simulation

Security impact assessment of industrial automation systems ...

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International Conference on Emerging Technologies and Factory automation (ETFA)

作者： Nikolaos Papakonstantinou Seppo Sierla Konstantinia Charitoudi Bryan O'Halloran Tommi Karhela Valeriy Vyatkin Irem Turner Department of Electrical Engineering and Automation Aalto University Finland Faculty of Computing Engineering and Science (FCES) University of South Wales UK School of Mechanical Industrial and Manufacturing Engineering Oregon State University OR USA VTT Technical Research Centre of Finland Finland Department of Computer Science Electrical and Space Engineering Luleå Tekniska Universitet Sweden Oregon State University Corvallis OR US

Much of the research on security of industrial automation systems has focused on countermeasures such as intrusion detection, certificate management or public key infrastructures. Due to limited resources, countermeasures should be focused to prevent the attacks with highest potential for damage. The impact of an attack can only be determined through a detailed analysis of the interactions of the automation system and the physical system under control. Attacks against single components are similar to ordinary component failures, so our focus is on deliberate damage to several components, since such scenarios are not considered in reliability engineering methods used for industrial automation systems. A simulation based security impact assessment method is proposed, using genetic algorithms to explore the range of possible attacks.

关键词： Genetic algorithms Computational modeling Biological cells Security automation Generators Inductors

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Towards an inclusive Parkinson's screening system

Towards an inclusive Parkinson's screening system

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International Conference on System Theory, Control, and computing (ICSTCC)

作者： Oana Geman Saeid Sanei Iuliana Chiuchisan Adrian Graur Aleš Procházka Oldřich Vyšata Department of Health and Human Development “Stefan eel Mare” University of Suceava Romania Department of Computer Science Electronics and Automation “Stefan cel Mare” University of Suceava Romania Faculty of Engineering and Physical Sciences University of Surrey United Kingdom Department of Computing and Control Engineering Institute of Chemical Technology Czech Republic Department of Neurology Charles University Czech Republic

In this study, brain, and gait dynamic information were combined and used for diagnosis and monitoring of Parkinson's disease (the most important Neurodegenerative Disorder). Analysis of the information corresponding to a prescribed movement involving tremor, and the related changes in brain connectivity is novel and original. Analytically, developing a space-time nonlinear adaptive system which fuses brain and gait information algorithmically is proposed here for the first time. The overall dynamic system will be constrained by the clinical impressions of the patient symptoms embedded in a knowledge-based system. The entire complex constrained problem were solved to enable a powerful model for recognition and monitoring of Parkinson's disease and establishing appropriate rules for its clinical following up.

关键词： Brain modeling Adaptation models Parkinson's disease Chaos Signal processing algorithms Nonlinear dynamical systems

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Instrumentation to detect contamination of insulating oil in motors applied to electrical submersible pump

Instrumentation to detect contamination of insulating oil in...

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IEEE/IAS International Conference on Industry Applications (INDUSCON)

作者： Andres O. Salazar Diego A. M. Fonsêca André L. Martelli Francisco Fontes Filipe de Oliveira Quintaes Department of Computing and Automation Engineering Federal University of Rio Grande do Norte Natal RN Brazil Universidade Federal do Rio Grande do Norte Natal RN BR Informatics Department Federal Institute of Rio Grande do Norte Natal RN Brazil

The purpose of this paper is to presents a design of a magnetic sensor capable of detecting contamination of insulating oil used in the artificial lift method of oil-type electrical submersible pump (ESP). The sensor generates an alarm signal at the moment when the contamination oil is present. This signal is transmitted to the surface by communication system which uses the tree-phase motor power. This diagnostic information enables the implementation of predictive maintenance (condition monitoring) functions. For plant operators, this therefore makes it possible to detect faults in advance and implement measures to improve operational reliability and keep the downtimes of plants to a minimum. The prototype was designed to work in harsh conditions to reach a depth of 2000 m and temperatures up to 200 C. It used simulator software to define the mechanical and electromagnetic variables. Results of field experiments were performed to validate the prototype. The final results performed in an ESP system with a 62-HP motor showed a good reliability and fast response of the prototype.

关键词： Magnetic flux Magnetic cores Induction motors Contamination Coils Oil insulation Ferrites

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Corrections to “Exploiting Web Images for Semantic Video Indexing Via Robust Sample-Specific Loss” [Oct 14 1677-1689]

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IEEE Transactions on Multimedia 2015年第2期17卷 256-256页

作者： Yang Yang Zheng-Jun Zha Yue Gao Xiaofeng Zhu Tat-Seng Chua School of Computer Science and Engineering University of Electronic Science and Technology of China Chengdu China Institute of Intelligent Machines Chinese Academy of Sciences Hefei China Department of Automation Tsinghua University China Biomedical Research Imaging Center University of North Carolina at Chapel Hill Chapel Hill United States School of Computing National University of Singapore Singapore

In the above paper [ibid, vol. 16, no. 6, p. 1679, Oct. 2014], the sentence "Yang et al. [?] integrated semisupervised learning and transfer learning techniques to exploit manually-labeled images for video tagging" should have appeared as "Yang et al. [34] integrated semisupervised learning and transfer learning techniques to exploit manually-labeled images for video tagging."

关键词： Iterative methods Indexing Video signal processing Learning (artificial intelligence) Image classification Tagging

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Operating limits of underexcited synchronous generator

Operating limits of underexcited synchronous generator

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2013 4th International Conference on Power engineering, Energy and Electrical Drives, POWERENG 2013

作者： Maljkovic, Zlatko Gasparac, Ivan University of Zagreb Faculty of Electrical Engineering and Computing Department of Electrical Machines Drives and Automation Zagreb Croatia

ISBN: (纸本)9781467363921

Standard power chart of synchronous generator has its limit defined by practical stability limit and by field current minimum in the underexcitation quadrant. However, during the time, some generators have shown certain sensitivity during the permanent underexcited operation even in the stabile operating area due to local heating of magnetic conductive parts in the end region of the machine. Underexcited operation is usually required in case of raised network voltage while the active power demands are lowered. Precise knowledge of limits of underexcited operation ability enables precise planning of system reactive power trading. Some world experiences and axial magnetic field measurements in the end region of synchronous hydro and turbine generator are presented. Based on mentioned measurements, it is possible to define real power chart which almost always deviates in capacitive operating area compared to manufacturer's diagram. © 2013 IEEE.

关键词： Turbogenerators

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Hybrid Bayesian estimation tree learning with discrete and fuzzy labels

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Frontiers of Computer Science 2013年第6期7卷 852-863页

作者： Zengchang QIN Tao WAN Intelligent Computing and Machine Learning Lab School of Automation Science and Electrical Engineering Beihang University Beijing 100191 China School of Biological Science and Medical Engineering Beihang University Beijing 100191 China Department of Biomedical Engineering Case Western Reserve University Cleveland OH 44106 USA

Classical decision tree model is one of the classical machine learning models for its simplicity and effectiveness in applications. However, compared to the DT model, probability estimation trees （PETs） give a better estimation on class probability. In order to get a good probability estimation, we usually need large trees which are not desirable with respect to model transparency. Linguistic decision tree （LDT） is a PET model based on label semantics. Fuzzy labels are used for building the tree and each branch is associated with a probability distribution over classes. If there is no overlap between neighboring fuzzy labels, these fuzzy labels then become discrete labels and a LDT with discrete labels becomes a special case of the PET model. In this paper, two hybrid models by combining the naive Bayes classifier and PETs are proposed in order to build a model with good performance without losing too much transparency. The first model uses naive Bayes estimation given a PET, and the second model uses a set of small-sized PETs as estimators by assuming the independence between these trees. Empirical studies on discrete and fuzzy labels show that the first model outperforms the PET model at shallow depth, and the second model is equivalent to the naive Bayes and PET.

关键词： fuzzy labels label semantics random set probability estimation tree mass assignment linguistic decision tree naive Bayes

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Selecting redundant nodes when addressing availability in wireless visual sensor networks

Selecting redundant nodes when addressing availability in wi...

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IEEE International Conference on Industrial Informatics (INDIN)

作者： Daniel G. Costa Ivanovitch Silva Luiz Affonso Guedes Paulo Portugal Francisco Vasques Department of Technology State University of Feira de Santana Feira de Santana Brazil Department of Computing and Automation Federal University of Rio Grande do Norte Natal Brazil Universidade Federal do Rio Grande do Norte Natal RN BR Faculty of Engineering University of Porto Porto Portugal

As Wireless Sensor Networks have been employed to support critical monitoring applications, network availability has become a major design concern. In these networks, redundancy can be exploited to enhance the attainable availability level, where redundant sensors can replace faulty nodes. When camera-enabled sensors are deployed to retrieve visual information, the perception of redundancy changes considerably, since the redundancy of visual sensors depends on the monitoring requirements of the applications. In such context, characteristics as deployment density, viewing angle and sensing range are relevant when planning wireless sensor network applications, directly impacting in the number of redundant nodes. We propose an algorithm to select redundant nodes in Wireless Visual Sensor Networks, according to the application requirements. Moreover, we discuss how parameters of the deployed network can influence on the number of redundant nodes.

关键词： Visualization Redundancy Monitoring Sensors Availability Wireless sensor networks Wireless communication

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Parallel architecture and optimization for discrete-event simulation of spike neural networks

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Science China(Technological Sciences) 2013年第2期56卷 509-517页

作者： TANG YuHua ZHANG BaiDa WU JunJie HU TianJiang ZHOU Jing LIU FuDong Department of Computer Science and Technology School of ComputerNational University of Defense Technology State Key Laboratory of High Performance Computing National University of Defense Technology College of Mechatronic Engineering and Automation National University of Defense Technology

Spike neural networks are inspired by animal brains,and outperform traditional neural networks on complicated ***,spike neural networks are usually used on a large scale,and they cannot be computed on commercial,off-the-shelf computers.A parallel architecture is proposed and developed for discrete-event simulations of spike neural ***,mechanisms for both parallelism degree estimation and dynamic load balance are emphasized with theoretical and computational *** results show the effectiveness of the proposed parallelized spike neural network system and its corresponding support components.

关键词： spike neural network discrete event simulation intelligent parallelization framework

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