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Condition Monitoring and Assessment of Power Transformers Using Computational Intelligence

Condition Monitoring and Assessment of Power Transformers Using Computational Intelligence Author W.H. Tang
ISBN-10 0857290525
Release 2011-01-19
Pages 202
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In recent years, rapid changes and improvements have been witnessed in the field of transformer condition monitoring and assessment, especially with the advances in computational intelligence techniques. Condition Monitoring and Assessment of Power Transformers Using Computational Intelligence applies a broad range of computational intelligence techniques to deal with practical transformer operation problems. The approaches introduced are presented in a concise and flowing manner, tackling complex transformer modelling problems and uncertainties occurring in transformer fault diagnosis. Condition Monitoring and Assessment of Power Transformers Using Computational Intelligence covers both the fundamental theories and the most up-to-date research in this rapidly changing field. Many examples have been included that use real-world measurements and realistic operating scenarios of power transformers to fully illustrate the use of computational intelligence techniques for a variety of transformer modelling and fault diagnosis problems. Condition Monitoring and Assessment of Power Transformers Using Computational Intelligence is a useful book for professional engineers and postgraduate students. It also provides a firm foundation for advanced undergraduate students in power engineering.



Condition Assessment of High Voltage Insulation in Power System Equipment

Condition Assessment of High Voltage Insulation in Power System Equipment Author R.E. James
ISBN-10 9780863417375
Release 2008
Pages 276
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This book introduces the reader to the major components of a high voltage system and the different insulating materials applied in particular equipments. During a review of these materials, measurable properties suitable for condition assessment are identified. Analyses are included of some of the insulation fault scenarios that may occur in power equipment. The basic facilities for carrying out tests on the internal and external insulation structures at high and low voltages are described. Tests and measurements according to specifications, on-site requirements and research investigations are considered.Advances in the application of digital techniques for detection and analyses of partial discharges are discussed and methods in use, or under development, for service condition monitoring are described. These include the utilisation of new sensors, the solution of online problems associated with noise rejection and the adaptation of artificial intelligence techniques for incipient fault diagnosis.



Reliability in Power Electronics and Electrical Machines Industrial Applications and Performance Models

Reliability in Power Electronics and Electrical Machines  Industrial Applications and Performance Models Author Kaboli, Shahriyar
ISBN-10 9781466694309
Release 2016-03-08
Pages 481
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In modern industries, electrical energy conversion systems consist of two main parts: electrical machines and power electronic converters. With global electricity use at an all-time high, uninterrupted operation of electrical power converters is essential. Reliability in Power Electronics and Electrical Machines: Industrial Applications and Performance Models provides an in-depth analysis of reliability in electrical energy converters as well as strategies for designing dependable power electronic converters and electrical machines. Featuring a comprehensive discussion on the topics of reliability design and measurement, failure mechanisms, and specific issues pertaining to quality, efficiency, and durability, this timely reference source offers practical examples and research-based results for use by engineers, researchers, and advanced-level students.



Condition Monitoring Using Computational Intelligence Methods

Condition Monitoring Using Computational Intelligence Methods Author Tshilidzi Marwala
ISBN-10 9781447123798
Release 2012-01-23
Pages 236
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Condition Monitoring Using Computational Intelligence Methods promotes the various approaches gathered under the umbrella of computational intelligence to show how condition monitoring can be used to avoid equipment failures and lengthen its useful life, minimize downtime and reduce maintenance costs. The text introduces various signal-processing and pre-processing techniques, wavelets and principal component analysis, for example, together with their uses in condition monitoring and details the development of effective feature extraction techniques classified into frequency-, time-frequency- and time-domain analysis. Data generated by these techniques can then be used for condition classification employing tools such as: • fuzzy systems; rough and neuro-rough sets; neural and Bayesian networks;hidden Markov and Gaussian mixture models; and support vector machines.



Recent Trends in the Condition Monitoring of Transformers

Recent Trends in the Condition Monitoring of Transformers Author Sivaji Chakravorti
ISBN-10 9781447155508
Release 2013-10-21
Pages 280
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Recent Trends in the Condition Monitoring of Transformers reflects the current interest in replacing traditional techniques used in power transformer condition monitoring with non-invasive measures such as polarization/depolarization current measurement, recovery voltage measurement, frequency domain spectroscopy and frequency response analysis. The book stresses the importance of scrutinizing the condition of transformer insulation which may fail under present day conditions of intensive use with the resulting degradation of dielectric properties causing functional failure of the transformer. The text shows the reader how to overcome the key challenges facing today’s maintenance policies, namely: The selection of appropriate techniques for dealing with each type of failure process accounting for the needs of plant owners, plant users and wider society; and Cost-efficiency and durability of effect. Many of the failure-management methods presented rely on the fact that most failures give warning when they are imminent. These potential failures give rise to identifiable physical conditions and the novel approaches described detect them so that action can be taken to avoid degeneration into full-blown functional failure. This “on-condition” maintenance means that equipment can be left in service as long as a specified set of performance standards continue to be met, avoiding the costly downtime imposed by routine and perhaps unnecessary maintenance but without risking equally expensive failure. Recent Trends in the Condition Monitoring of Transformers will be of considerable interest to both academic researchers in power systems and to engineers working in the power generation and distribution industry showing how new and more efficient methods of fault diagnosis and condition management can increase transformer efficiency and cut costs.



Advances in System Optimization and Control

Advances in System Optimization and Control Author Sri Niwas Singh
ISBN-10 9789811306655
Release 2018-06-08
Pages 268
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This book comprises select proceedings of the International Conference on Advancement in Energy, Drives, and Control. It covers frontier topics in optimization and control. It covers applications of optimization processes in areas such as computer architecture, communication systems, system optimization, signal processing, fluid dynamics and process control. This book is of use to researchers, professionals, and students from across engineering disciplines.



Dynamic Vulnerability Assessment and Intelligent Control

Dynamic Vulnerability Assessment and Intelligent Control Author José Luis Rueda-Torres
ISBN-10 9781119214977
Release 2018-01-25
Pages 448
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Identifying, assessing, and mitigating electric power grid vulnerabilities is a growing focus in short-term operational planning of power systems. Through illustrated application, this important guide surveys state-of-the-art methodologies for the assessment and enhancement of power system security in short term operational planning and real-time operation. The methodologies employ advanced methods from probabilistic theory, data mining, artificial intelligence, and optimization, to provide knowledge-based support for monitoring, control (preventive and corrective), and decision making tasks. Key features: Introduces behavioural recognition in wide-area monitoring and security constrained optimal power flow for intelligent control and protection and optimal grid management. Provides in-depth understanding of risk-based reliability and security assessment, dynamic vulnerability assessment methods, supported by the underpinning mathematics. Develops expertise in mitigation techniques using intelligent protection and control, controlled islanding, model predictive control, multi-agent and distributed control systems Illustrates implementation in smart grid and self-healing applications with examples and real-world experience from the WAMPAC (Wide Area Monitoring Protection and Control) scheme. Dynamic Vulnerability Assessment and Intelligent Control for Power Systems is a valuable reference for postgraduate students and researchers in power system stability as well as practicing engineers working in power system dynamics, control, and network operation and planning.



Condition Monitoring Using Computational Intelligence Methods

Condition Monitoring Using Computational Intelligence Methods Author Tshilidzi Marwala
ISBN-10 9781447123798
Release 2012-01-23
Pages 236
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Condition Monitoring Using Computational Intelligence Methods promotes the various approaches gathered under the umbrella of computational intelligence to show how condition monitoring can be used to avoid equipment failures and lengthen its useful life, minimize downtime and reduce maintenance costs. The text introduces various signal-processing and pre-processing techniques, wavelets and principal component analysis, for example, together with their uses in condition monitoring and details the development of effective feature extraction techniques classified into frequency-, time-frequency- and time-domain analysis. Data generated by these techniques can then be used for condition classification employing tools such as: • fuzzy systems; rough and neuro-rough sets; neural and Bayesian networks;hidden Markov and Gaussian mixture models; and support vector machines.



Spotlight on Modern Transformer Design

Spotlight on Modern Transformer Design Author Pavlos Stylianos Georgilakis
ISBN-10 9781848826670
Release 2009-07-30
Pages 427
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Spotlight on Modern Transformer Design introduces a novel approach to transformer design using artificial intelligence (AI) techniques in combination with finite element method (FEM). Today, AI is widely used for modeling nonlinear and large-scale systems, especially when explicit mathematical models are difficult to obtain or completely lacking. Moreover, AI is computationally efficient in solving hard optimization problems. Many numerical examples throughout the book illustrate the application of the techniques discussed to a variety of real-life transformer design problems, including: • problems relating to the prediction of no-load losses; • winding material selection; • transformer design optimisation; • and transformer selection. Spotlight on Modern Transformer Design is a valuable learning tool for advanced undergraduate and graduate students, as well as researchers and power engineering professionals working in electric utilities and industries, public authorities, and design offices.



Artificial Intelligence Tools

Artificial Intelligence Tools Author Diego Galar Pascual
ISBN-10 9781466584068
Release 2015-04-22
Pages 549
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Artificial Intelligence Tools: Decision Support Systems in Condition Monitoring and Diagnosis discusses various white- and black-box approaches to fault diagnosis in condition monitoring (CM). This indispensable resource: Addresses nearest-neighbor-based, clustering-based, statistical, and information theory-based techniques Considers the merits of each technique as well as the issues associated with real-life application Covers classification methods, from neural networks to Bayesian and support vector machines Proposes fuzzy logic to explain the uncertainties associated with diagnostic processes Provides data sets, sample signals, and MATLAB® code for algorithm testing Artificial Intelligence Tools: Decision Support Systems in Condition Monitoring and Diagnosis delivers a thorough evaluation of the latest AI tools for CM, describing the most common fault diagnosis techniques used and the data acquired when these techniques are applied.



Intelligent Industrial Systems Modeling Automation and Adaptive Behavior

Intelligent Industrial Systems  Modeling  Automation and Adaptive Behavior Author Rigatos, Gerasimos
ISBN-10 9781615208500
Release 2010-06-30
Pages 601
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In recent years, there has been growing interest in industrial systems, especially in robotic manipulators and mobile robot systems. As the cost of robots goes down and become more compact, the number of industrial applications of robotic systems increases. Moreover, there is need to design industrial systems with intelligence, autonomous decision making capabilities, and self-diagnosing properties. Intelligent Industrial Systems: Modeling, Automation and Adaptive Behavior analyzes current trends in industrial systems design, such as intelligent, industrial, and mobile robotics, complex electromechanical systems, fault diagnosis and avoidance of critical conditions, optimization, and adaptive behavior. This book discusses examples from major areas of research for engineers and researchers, providing an extensive background on robotics and industrial systems with intelligence, autonomy, and adaptive behavior giving emphasis to industrial systems design.



Protective Relaying of Power Systems Using Mathematical Morphology

Protective Relaying of Power Systems Using Mathematical Morphology Author Q.H. Wu
ISBN-10 9781848824997
Release 2009-05-06
Pages 208
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This book discusses the development of novel protective relaying algorithms using Mathematical Morphology, a nonlinear signal processing technique derived from set theory and geometry.



High Voltage Engineering and Testing

High Voltage Engineering and Testing Author Hugh McLaren Ryan
ISBN-10 0852967756
Release 2001-01-01
Pages 726
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High voltage, Electrical engineering, Electronic engineering, Electrical testing, Building and Construction



Estimating the Transformer Health Index Using Artificial Intelligence Techniques

Estimating the Transformer Health Index Using Artificial Intelligence Techniques Author Alhaytham Y. Al Qudsi
ISBN-10 OCLC:985968159
Release 2016
Pages 81
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"Transformer Asset Management (TAM) is concerned with the strategic activities that monitor and manage the transformer asset in the power system. The outcomes of TAM aim at setting proper monitoring methods and maintenance plans, with minimal cost of time and money. Monitoring methods in the form of electrical, chemical and physical tests are conducted to assess the transformer operational condition. The main part, which is directly related to the ageing of the transformer, is the oil-paper insulation system. The standard practiced monitoring test methods used by TAM companies are considered highly effective and useful. However, a full feedback of the transformer’s condition requires a number of monitoring tests to be conducted. Such an exercise is considered expensive and difficult to implement for some of the tests. Moreover, the individual conducted tests cannot provide a comprehensive understanding of the transformer condition based on a single factor. Thus, the concept of the Health Index (HI) was developed to accurately assess the transformer’s condition and effective remnant age. The main components involved in the HI computation are related to the transformers' insulation condition, service record and design. Finding the transformer HI is normally done through using several industry computational methods. The drawback of these methods is the large number of tests required to achieve high level of condition assessment accuracy. Thus, alternative Artificially Intelligent (AI) methods should be used to design the HI model. AI methods, such as Artificial Neural Networks (ANN), can learn the pattern of the response output (HI), based on a given set of input (monitoring tests). The use of feature selection technique such as stepwise regression, can lead to an effective reduction of redundant tests in the presence of more significant ones. The presented work produces a general cost-effective AI based HI predictor model that can be used by different utility companies. Such a predictor would be able to produce a HI output value with a 95% prediction accuracy using only a subset of the required input features. Furthermore, the model can produce the same prediction accuracy with a predicted costly feature as one of the input features."--Abstract.



Advances in Computer Science and Information Engineering

Advances in Computer Science and Information Engineering Author David Jin
ISBN-10 9783642302237
Release 2012-05-11
Pages 715
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CSIE2012 is an integrated conference concentrating its focus on Computer Science and Information Engineering . In the proceeding, you can learn much more knowledge about Computer Science and Information Engineering of researchers from all around the world. The main role of the proceeding is to be used as an exchange pillar for researchers who are working in the mentioned fields. In order to meet the high quality of Springer, AISC series, the organization committee has made their efforts to do the following things. Firstly, poor quality paper has been refused after reviewing course by anonymous referee experts. Secondly, periodically review meetings have been held around the reviewers about five times for exchanging reviewing suggestions. Finally, the conference organizers had several preliminary sessions before the conference. Through efforts of different people and departments, the conference will be successful and fruitful.



Power Systems Signal Processing for Smart Grids

Power Systems Signal Processing for Smart Grids Author Paulo Fernando Ribeiro
ISBN-10 9781118639238
Release 2013-09-20
Pages 448
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With special relation to smart grids, this book provides clear and comprehensive explanation of how Digital Signal Processing (DSP) and Computational Intelligence (CI) techniques can be applied to solve problems in the power system. Its unique coverage bridges the gap between DSP, electrical power and energy engineering systems, showing many different techniques applied to typical and expected system conditions with practical power system examples. Surveying all recent advances on DSP for power systems, this book enables engineers and researchers to understand the current state of the art and to develop new tools. It presents: an overview on the power system and electric signals, with description of the basic concepts of DSP commonly found in power system problems the application of several signal processing tools to problems, looking at power signal estimation and decomposition, pattern recognition techniques, detection of the power system signal variations description of DSP in relation to measurements, power quality, monitoring, protection and control, and wide area monitoring a companion website with real signal data, several Matlab codes with examples, DSP scripts and samples of signals for further processing, understanding and analysis Practicing power systems engineers and utility engineers will find this book invaluable, as will researchers of electrical power and energy systems, postgraduate electrical engineering students, and staff at utility companies.



IP Network based Multi agent Systems for Industrial Automation

IP Network based Multi agent Systems for Industrial Automation Author David P. Buse
ISBN-10 9781846286476
Release 2007-02-23
Pages 187
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This book details the use of the Internet protocol suite and multi-agent systems for the information management, online monitoring, and control of distributed power system substations. It proposes an open architecture for information management and control, based on the concepts of multi-agent systems and mobile agents. Mobile agents are applied to the retrieval and analysis of substation data and to remote operator intervention.