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检索条件"机构=Knowledge and Intelligent Computing Laboratory"

共 114 条记录，以下是81-90 订阅

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Principal Component Analysis Anomaly Detector for Rotor Broken Bars

Principal Component Analysis Anomaly Detector for Rotor Brok...

引用

Annual Conference of the IEEE Industrial Electronics Society

作者： Mohammed Obaid Mustafa George Georgoulas George Nikolakopoulos Control Engineering Group Department of Computer Science Electrical and Space Engineering Lulea University of Technology Laboratory of Knowledge and Intelligent Computing (KIC) Department of Computer Engineering Technological Educational Institute of Epirus

ISBN: (纸本)9781479940318

In this article a method for the detection of broken rotor bars in asynchronous machines operating under full load is presented. Unlike most Motor Current Signature Analysis (MCSA) approaches, which operate in the frequency domain, our method operates in the time domain. The scheme is based on the use of a Principal Component Analysis (PCA) fault/anomaly detector. PCA is applied on the three stator currents to subsequently calculate the Q statistic which is employed for detecting the presence/absence of a fault. The efficiency of the proposed scheme was experimentally evaluated using different fault severity levels, ranging from 1/4 of a broken bar to three broken bars. The obtained results indicate that the method can detect the caused asymmetry with a very restricted amount of data.

关键词： Principal component analysis Rotors Bars Induction motors Detectors Stators Fault detection

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An automated thermographic image segmentation method for induction motor fault diagnosis

An automated thermographic image segmentation method for ind...

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作者： Karvelis, Petros Georgoulas, George Stylios, Chsysostomos D. Tsoumas, Ioannis P. Antonino-Daviu, Jose Alfonso Rodenas, Maria Jose Picazo Climente-Alarcon, Vicente Laboratory of Knowledge and Intelligent Computing Technological Educational Institute of Epirus Department of Computer Engineering Arta Greece Larges Drives Products RandD Department Siemens Industry Sector - Drive Technologies Nuremberg Germany Instituto de Ingeniería Energética Universitat Politècnica de València Valencia Spain Department of Electrical Engineering and Automation Aalto University Espoo Finland

ISBN: (纸本)9781479940325

Eventual failures in induction machines may lead to catastrophic consequences in terms of economic costs for the companies. The development of reliable systems for fault detection that enable to diagnose a wide range of faults is a motivation of many researchers worldwide. In this context, non-invasive condition monitoring strategies have drawn special attention since they do not require interfering with the operation process of the machine. Though the analysis of the motor currents has proven to be a reliable, non-invasive methodology to detect some of the faults (especially when assessing the rotor condition), it lacks reliability for the diagnosis of other faults (e.g. bearing faults). The infrared thermography has proven to be an excellent, non-invasive tool that can complement the diagnosis reached with the motor current analysis, especially for some specific faults. However, there are still some pending issues regarding its application to induction motor faults diagnosis, such as the lack of automation or the extraction of reliable fault indicators based on the infrared data. This paper proposes a methodology that intends to provide a solution to the first issue: a method based on image segmentation is employed to detect several failures in an automated way. Four specific faults are analyzed: bearing faults, fan failures, rotor bar breakages and stator unbalance. The results show the potential of the technique to automatically identify the fault present in the machine. © 2014 IEEE.

关键词： Image segmentation

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Fuzzy Cognitive Map Scenario-Based Medical Decision Support Systems for Education

Fuzzy Cognitive Map Scenario-Based Medical Decision Support ...

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Annual International Conference of the IEEE Engineering in Medicine and Biology Society

作者： Voula C. Georgopoulos Spyridoula Chouliara Chrysostomos D. Stylios Department of Speech and Language Therapy Technological Educational Institute of Western Greece Koukouli Patras Greece MSc is an Obstetrician working for a private Obstetrician and Gynecological Clinic Artas Greece Head of the Knowledge and Intelligent Computing Laboratory Technological Educational Institute of Epirus Artas Greece

Soft computing (SC) techniques are based on exploiting human knowledge and experience and they are extremely useful to model any complex decision making procedure. Thus, they have a key role in the development of Medical Decision Support Systems (MDSS). The soft computing methodology of Fuzzy Cognitive Maps has successfully been used to represent human reasoning and to infer conclusions and decisions in a human-like way and thus, FCM-MDSSs have been developed. Such systems are able to assist in critical decision-making, support diagnosis procedures and consult medical professionals. Here a new methodology is introduced to expand the utilization of FCM-MDSS for learning and educational purposes using a scenario-based learning (SBL) approach. This is particularly important in medical education since it allows future medical professionals to safely explore extensive "what-if' scenarios in case studies and prepare for dealing with critical adverse events.

关键词： Medical diagnostic imaging Fetal heart rate Decision support systems Decision making Fuzzy cognitive maps Education Biomedical monitoring

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Automatizing the broken bar detection process via Short Time Fourier Transform and two-dimensional Piecewise Aggregate Approximation representation

Automatizing the broken bar detection process via Short Time...

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IEEE Energy Conversion Congress and Exposition

作者： George Georgoulas Petros Karvelis Chysostomos D. Stylios Ioannis P. Tsoumas Jose Alfonso Antonino-Daviu Vicente Climente-Alarcon Laboratory of Knowledge and Intelligent Computing Department of Computer Engineering TEI of Epirus 47100 Artas Kostakioi Greece Larges Drives R&D Department Siemens Industry Sector - Drive Technologies Nuremberg Germany Instituto de Ingenieria Energetica Universitat Politecnica de Valencia Valencia Spain

ISBN: (纸本)9781479957774

This work presents an automated approach for detecting broken rotor bars in induction machines using the stator current during startup operation. The currents are analyzed using the well-known Short Time Fourier Transform (STFT) producing a two-dimensional time-frequency representation. This representation contains information regarding the presence of a characteristic transient component but requires further processing before it can be fed into a standard classification algorithm. In this work, this part is performed using the two dimensional extension of Piecewise Aggregate Approximation (PAA) that can deal with the two dimensional representation of STFT. The results (with both simulated and experimental data) suggest that the method can be used for the automatic detection of broken bars and even for determining the fault severity. Moreover, its low computational burden makes it ideal for its future use in online, unsupervised systems, as well as in portable condition monitoring devices.

关键词： Time-frequency analysis Bars Transient analysis Rotors Circuit faults Spectrogram Stators

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An Automated Thermographic Image Segmentation Method for Induction Motor Fault Diagnosis

An Automated Thermographic Image Segmentation Method for Ind...

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Annual Conference of the IEEE Industrial Electronics Society

作者： Petros Karvelis George Georgoulas Chsysostomos D. Stylios Ioannis P. Tsoumas Jose Alfonso Antonino-Daviu Maria Jose Picazo Rodenas Vicente Climente-Alarcon Laboratory of Knowledge and Intelligent Computing Technological Educational Institute of Epirus Department of Computer Engineering Larges Drives Products R&D Department Siemens Industry Sector - Drive Technologies Instituto de Ingenieria Energetica Universitat Politecnica de Valencia Department of Electrical Engineering and Automation Aalto University

ISBN: (纸本)9781479940318

关键词： Induction motor Fault diagnosis SIFT Image segmentation Object matching

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An adaptive method for the recovery of missing samples from FHR time series

An adaptive method for the recovery of missing samples from ...

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IEEE International Symposium on Computer-Based Medical Systems

作者： Vangelis P. Oikonomou Jiri Spilka Chrysostomos Stylios Lenka Lhostka Laboratory of Knowledge and Intelligent Computing Department of Informatics and Telecommunication Technology TEI of Epirus 47100 Arta Greece

ISBN: (纸本)9781479910526

Missing data cause serious problem for automatic evaluation of the fetal heart rate(FHR) series. In this work we present an algorithm to surpress this problem. More specifically, an adaptive approach is proposed based on two steps. The first step concerns the reconstruction step where we obtain an estimate of the missing data using an empirical dictionary. The second step consists from the construction of the dictionary using the updated values from the first step. The above two steps are applied iteratively until convergence. The method adapts each time the dictionary and the reconstructed time series to the new information that we gain. Results on real and simulated experiments have shown the usefullness of our approach. More specifically, a comparison with cubic spline interpolation is performed and have shown that the proposed approach achieved 4 to 9dB better reconstruction ability.

关键词： method recovery samples

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Modeling complex logistics systems using soft computing methodology of fuzzy cognitive maps

Modeling complex logistics systems using soft computing meth...

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2011 7th IEEE International Conference on Automation Science and Engineering, CASE 2011

作者： Stylios, Chrysostomos D. Georgoulas, George Knowledge and Intelligent Computing Laboratory Dept. of Informatics and Telecommunications Technology Technological Educational Institute of Epirus 47100 Artas Greece

ISBN: (纸本)9781457717307

Fuzzy Cognitive Maps (FCMs) is an abstract soft computing modeling methodology that has been applied in many areas quite successfully. In this paper we discuss its modeling applicability to complex logistics systems involved in an intermodal container terminal and the way it could represent and handle the vast amount of information by an abstract point of view based on a decentralized approach, where the supervisor of the system is modeled as an FCM. We also investigate its applicability as a metamodel of the intermodal terminal in a simulation-optimization framework. Experts have a key role in developing the FCM as they describe a general operational and behavioral model of the system using concepts for the main aspects of the system, and weighted directed edges to represent causality. On the other hand, when data is available, data driven approaches have also been proposed for the development of FCM models. The FCM representation and implementation is discussed to develop a behavioral model of any complex system mainly based on a hierarchical structure, as well as its use as a metamodel of the system. © 2011 IEEE.

关键词： Fuzzy Cognitive Maps

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Rotor Fault Diagnosis in Asynchronous Machines via Analysis of the Start-Up Transient into Intrinsic Mode Functions

Rotor Fault Diagnosis in Asynchronous Machines via Analysis ...

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International Conference on Electrical Machines

作者： George Georgoulas Ioannis Tsoumas Epaminondas Mitronikas Chrysostomos D. Stylios Athanasios Safacas Laboratory of Knowledge and Intelligent Computing Dept. of Informatics and Communications Technology TEI of Epirus 47100 Arta Kostakioi Greece Siemens Industry Sector Automation and Drives Large Drives Nuremberg Germany Electromechanical Energy Conversion Laboratory Elec. and Comp. Eng. Dept. University of Patras Rio-Patras Greece

ISBN: (纸本)9781467301435

A novel approach for rotor fault diagnosis during the start-up process is proposed. Rotor faults create asymmetries that affect the phase currents in a subtle yet distinctive way. The approach presented here is based on the application of Empirical Mode Decomposition (EMD) to the measured start-up current for the extraction of a specific complex Intrinsic Mode Function (IMF). The characteristics of this particular IMF are quite distinct for the case of an asynchronous machine with rotor asymmetry and can be used to discriminate between faulty and healthy machines. This task of fault diagnosis is performed via the use of two Hidden Markov Models (HMMs) which are well known for their temporal pattern recognition capabilities. Simulation and experimental data demonstrate the effectiveness of the proposed methodology for the detection of rotor asymmetries.

关键词： Rotor Fault Diagnosis Asynchronous Machines Start-Up Transient

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Medical Decision Support Systems based on Soft computing techniques

Medical Decision Support Systems based on Soft Computing tec...

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作者： Stylios, Chrysostomos D. Georgopoulos, Voula C. Knowledge and Intelligent Computing Laboratory Department of Informatics and Telecommunications Technology Technological Educational Institute of Epirus 47100 Artas Greece Department of Speech and Language Therapy Technological Educational Institute of Patras Koukouli 26334 Patras Greece

ISBN: (纸本)9783902661937

Medical Decision Support Systems (MDSS) are very important constructions that are incorporated into intelligent Information E-Health Systems aiming to produce warnings or to consult and suggest clinical judgments either to inexperienced medical professionals or in their lighter versions to the general public through medical advisors websites. Soft computing (SC) techniques, especially those that are based on exploiting human knowledge and experience, are extremely useful to model complex decision making procedures and thus, they have a key role in development such MDSS. Such a modeling methodology is Fuzzy Cognitive Maps which is suitable to represent human reasoning and to infer conclusions and decisions in a human-like way. In order to develop an integrated stand alone MDSS, Fuzzy Cognitive Maps could be complemented by other Soft computing techniques such as Genetic Algorithms and/or Case Based Reasoning and so to construct more efficient advanced Medical Decision Support Systems. The synergism and complementary of these methodologies may pave the way to new sophisticated systems. © 2011 IFAC.

关键词： Fuzzy Cognitive Maps

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Modeling complex logistics systems using soft computing methodology of Fuzzy Cognitive Maps

Modeling complex logistics systems using soft computing meth...

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IEEE International Conference on Automation Science and Engineering (CASE)

作者： Chrysostomos D. Stylios George Georgoulas Knowledge and Intelligent Computing Laboratory Department of Informatics and Telecommunications Technology Technological Educational Institute of Epirus Artas Greece

关键词： Logistics Adaptation models Containers Computational modeling Humans Mathematical model Neural networks

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