Predictive Maintenance Of Wind Generators Based On Ai Techniques

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Predictive Maintenance of Wind Generators Based on AI Techniques

Author : Emin Elmar oglu Mammadov
Publisher :
ISBN 13 :
Total Pages : pages
Book Rating : 4.:/5 (126 download)

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Book Synopsis Predictive Maintenance of Wind Generators Based on AI Techniques by : Emin Elmar oglu Mammadov

Download or read book Predictive Maintenance of Wind Generators Based on AI Techniques written by Emin Elmar oglu Mammadov and published by . This book was released on 2019 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: As global warming is slowly becoming a dangerous reality, governments and private institutions are introducing policies to minimize it. Those policies have led to the development and deployment of Renewable Energy Sources (RESs), which introduces new challenges, among which the minimization of downtime and Levelised Cost of Energy (LCOE) by optimizing maintenance strategy where early detection of incipient faults is of significant intent. Hence, this is the focus of this thesis. While there are several maintenance approaches, predictive maintenance can utilize SCADA readings from large scale power plants to detect early signs of failures, which can be characterized by abnormal patterns in the measurements. There exists several approaches to detect these patterns such as model-based or hybrid techniques, but these require the detailed knowledge of the analyzed system. As SCADA system collects large amounts of data, machine learning techniques can be used to detect the underlying failure patterns and notify customers of the abnormal behaviour. In this work, a novel framework based on machine learning techniques for fault prediction of wind farm generators is developed for an actual customer. The proposed fault prognosis methodology addresses data limitation such as class imbalance and missing data, performs statistical tests on time series to test for its stationarity, selects the features with the most predictive power, and applies machine learning models to predict a fault with 1 hour horizon. The proposed techniques are tested and validated using historical data for a wind farm in Summerside, Prince Edward Island (PEI), Canada, and models are evaluated based on appropriate evaluation metrics. The results demonstrate the ability of the proposed methodology to predict wind generator failures, and the viability of the proposed methodology for optimizing preventive maintenance strategies.

Introduction to AI Techniques for Renewable Energy System

Author : Suman Lata Tripathi
Publisher : CRC Press
ISBN 13 : 1000392457
Total Pages : 423 pages
Book Rating : 4.0/5 (3 download)

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Book Synopsis Introduction to AI Techniques for Renewable Energy System by : Suman Lata Tripathi

Download or read book Introduction to AI Techniques for Renewable Energy System written by Suman Lata Tripathi and published by CRC Press. This book was released on 2021-11-25 with total page 423 pages. Available in PDF, EPUB and Kindle. Book excerpt: Introduction to AI techniques for Renewable Energy System Artificial Intelligence (AI) techniques play an essential role in modeling, analysis, and prediction of the performance and control of renewable energy. The algorithms used to model, control, or predict performances of the energy systems are complicated, involving differential equations, enormous computing power, and time requirements. Instead of complex rules and mathematical routines, AI techniques can learn critical information patterns within a multidimensional information domain. Design, control, and operation of renewable energy systems require a long-term series of meteorological data such as solar radiation, temperature, or wind data. Such long-term measurements are often non-existent for most of the interest locations or, wherever they are available, they suffer from several shortcomings, like inferior quality of data, and in-sufficient long series. The book focuses on AI techniques to overcome these problems. It summarizes commonly used AI methodologies in renewal energy, with a particular emphasis on neural networks, fuzzy logic, and genetic algorithms. It outlines selected AI applications for renewable energy. In particular, it discusses methods using the AI approach for prediction and modeling of solar radiation, seizing, performances, and controls of the solar photovoltaic (PV) systems. Features Focuses on a significant area of concern to develop a foundation for the implementation of renewable energy system with intelligent techniques Showcases how researchers working on renewable energy systems can correlate their work with intelligent and machine learning approaches Highlights international standards for intelligent renewable energy systems design, reliability, and maintenance Provides insights on solar cell, biofuels, wind, and other renewable energy systems design and characterization, including the equipment for smart energy systems This book, which includes real-life examples, is aimed at undergraduate and graduate students and academicians studying AI techniques used in renewal energy systems.

Maintenance Management of Wind Turbines

Author : Fausto Pedro García Márquez
Publisher : MDPI
ISBN 13 : 3039366297
Total Pages : 394 pages
Book Rating : 4.0/5 (393 download)

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Book Synopsis Maintenance Management of Wind Turbines by : Fausto Pedro García Márquez

Download or read book Maintenance Management of Wind Turbines written by Fausto Pedro García Márquez and published by MDPI. This book was released on 2020-12-06 with total page 394 pages. Available in PDF, EPUB and Kindle. Book excerpt: “Maintenance Management of Wind Turbines” considers the main concepts and the state-of-the-art, as well as advances and case studies on this topic. Maintenance is a critical variable in industry in order to reach competitiveness. It is the most important variable, together with operations, in the wind energy industry. Therefore, the correct management of corrective, predictive and preventive politics in any wind turbine is required. The content also considers original research works that focus on content that is complementary to other sub-disciplines, such as economics, finance, marketing, decision and risk analysis, engineering, etc., in the maintenance management of wind turbines. This book focuses on real case studies. These case studies concern topics such as failure detection and diagnosis, fault trees and subdisciplines (e.g., FMECA, FMEA, etc.) Most of them link these topics with financial, schedule, resources, downtimes, etc., in order to increase productivity, profitability, maintainability, reliability, safety, availability, and reduce costs and downtime, etc., in a wind turbine. Advances in mathematics, models, computational techniques, dynamic analysis, etc., are employed in analytics in maintenance management in this book. Finally, the book considers computational techniques, dynamic analysis, probabilistic methods, and mathematical optimization techniques that are expertly blended to support the analysis of multi-criteria decision-making problems with defined constraints and requirements.

Advances in Artificial Intelligence for Renewable Energy Systems and Energy Autonomy

Author : Mukhdeep Singh Manshahia
Publisher : Springer Nature
ISBN 13 : 3031264967
Total Pages : 302 pages
Book Rating : 4.0/5 (312 download)

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Book Synopsis Advances in Artificial Intelligence for Renewable Energy Systems and Energy Autonomy by : Mukhdeep Singh Manshahia

Download or read book Advances in Artificial Intelligence for Renewable Energy Systems and Energy Autonomy written by Mukhdeep Singh Manshahia and published by Springer Nature. This book was released on 2023-06-14 with total page 302 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book provides readers with emerging research that explores the theoretical and practical aspects of implementing new and innovative artificial intelligence (AI) techniques for renewable energy systems. The contributions offer broad coverage on economic and promotion policies of renewable energy and energy-efficiency technologies, the emerging fields of neuro-computational models and simulations under uncertainty (such as fuzzy-based computational models and fuzzy trace theory), evolutionary computation, metaheuristics, machine learning applications, advanced optimization, and stochastic models. This book is a pivotal reference for IT specialists, industry professionals, managers, executives, researchers, scientists, and engineers seeking current research in emerging perspectives in artificial intelligence, renewable energy systems, and energy autonomy.

Zephyr

Author : Frances R. Hartwell
Publisher :
ISBN 13 :
Total Pages : 0 pages
Book Rating : 4.:/5 (139 download)

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Book Synopsis Zephyr by : Frances R. Hartwell

Download or read book Zephyr written by Frances R. Hartwell and published by . This book was released on 2023 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: Because wind turbines often operate through harsh weather events, under variable operating conditions, and in difficult-to-access locations, turbine maintenance is often challenging and costly. In this thesis, we present Zephyr, a flexible machine learning framework for predictive maintenance of wind energy assets. Manual analysis of wind turbine data is difficult and time-consuming due to its volume, variety, and, most importantly, the need for quick detection of issues. Machine learning (ML) methods are able to automate large-scale data analysis. However, the enormous amount of contextual information required to actually understand the data impedes the ability of ML frameworks to provide actionable insights. To this end, Zephyr enables Subject Matter Experts (SMEs) to incorporate their knowledge at various stages of ML model development. The Zephyr framework consists of a signal-processing-based featurization library, a data labeling algorithm - which helps analyze operational data and maintenance events in order to create labels for machine learning problems - and a set of automated machine learning pipelines for predicting outcome types. SMEs incorporate their expertise by providing labeling functions, bands for frequency domain-based featurization, and several other inputs in an intuitive way. We demonstrate the efficacy of this framework through two case studies involving maintenance operation data from wind turbines. Moreover, we show that ML performance can increase when involving domain expertise by a value as high as 48%.

A Machine Learning Framework for Predictive Maintenance of Wind Turbines

Author : Katherine Yuchen Wang
Publisher :
ISBN 13 :
Total Pages : 75 pages
Book Rating : 4.:/5 (123 download)

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Book Synopsis A Machine Learning Framework for Predictive Maintenance of Wind Turbines by : Katherine Yuchen Wang

Download or read book A Machine Learning Framework for Predictive Maintenance of Wind Turbines written by Katherine Yuchen Wang and published by . This book was released on 2020 with total page 75 pages. Available in PDF, EPUB and Kindle. Book excerpt: Wind energy is one of the fastest growing energy sources in the world. However, the failure to detect the breakdown of turbine parts can be very costly. Wind energy companies have increasingly turned to machine learning to improve wind turbine reliability. Thus, the goal of this thesis is to create a flexible and extensible machine learning framework that enables wind energy experts to define and build models for the predictive maintenance of wind turbines. We contribute two libraries that provide experts with the necessary tools to solve prediction problems in the wind energy industry. The first is GPE, which translates and uses the desired prediction problem to generate machine learning training examples from turbine operations data. The other library, CMS-ML, provides the architecture for building machine learning models using vibration data generated by turbine sensors within the Condition Monitoring System (CMS). With this architecture, we can easily create modular feature engineering and machine learning pipelines for the CMS signal data. Finally, we demonstrate the application of these two libraries on proprietary wind turbine data and analyze the effects of their parameters.

Data Science for Wind Energy

Author : Yu Ding
Publisher : CRC Press
ISBN 13 : 0429956517
Total Pages : 400 pages
Book Rating : 4.4/5 (299 download)

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Book Synopsis Data Science for Wind Energy by : Yu Ding

Download or read book Data Science for Wind Energy written by Yu Ding and published by CRC Press. This book was released on 2019-06-04 with total page 400 pages. Available in PDF, EPUB and Kindle. Book excerpt: Data Science for Wind Energy provides an in-depth discussion on how data science methods can improve decision making for wind energy applications, near-ground wind field analysis and forecast, turbine power curve fitting and performance analysis, turbine reliability assessment, and maintenance optimization for wind turbines and wind farms. A broad set of data science methods covered, including time series models, spatio-temporal analysis, kernel regression, decision trees, kNN, splines, Bayesian inference, and importance sampling. More importantly, the data science methods are described in the context of wind energy applications, with specific wind energy examples and case studies. Please also visit the author’s book site at https://aml.engr.tamu.edu/book-dswe. Features Provides an integral treatment of data science methods and wind energy applications Includes specific demonstration of particular data science methods and their use in the context of addressing wind energy needs Presents real data, case studies and computer codes from wind energy research and industrial practice Covers material based on the author's ten plus years of academic research and insights

Ethical Artificial Intelligence in Power Electronics

Author : Tarandeep Kaur Bhatia
Publisher : CRC Press
ISBN 13 : 1040091016
Total Pages : 204 pages
Book Rating : 4.0/5 (4 download)

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Book Synopsis Ethical Artificial Intelligence in Power Electronics by : Tarandeep Kaur Bhatia

Download or read book Ethical Artificial Intelligence in Power Electronics written by Tarandeep Kaur Bhatia and published by CRC Press. This book was released on 2024-08-01 with total page 204 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book focuses on the techniques of artificial intelligence that are mainly used in the power electronics field for the optimization of lost vehicle power. With the intention of optimizing the powerful energy of the vehicles and producing reliable energy, the most efficient methods, algorithms, and strategies of ethical artificial intelligence (AI) are being applied. By employing machine learning methods, the optimization of power energy in vehicles can be quickly recovered and managed efficiently. In today’s bustling world, power energy is indispensable for progress, yet in congested Vehicular Ad-hoc Networks (VANETs), vehicles often face power depletion and decreased efficiency. This book explores these challenges, encompassing not only power but also other critical power electronics within vehicles. We aim to introduce innovative approaches, leveraging ethical AI methods, to optimize energy performance in the face of these difficulties. Through this exploration, we seek to provide practical insights into navigating congested VANET environments while upholding ethical principles in technological advancements. Our book will discuss the current power energy concerns faced by vehicles and also contribute a novel strategy to overcome those concerns. The employment of ethical AI in vehicular power energy will undoubtedly improve the effectiveness and production of vehicles.

Artificial Intelligence for Renewable Energy Systems

Author : Ajay Kumar Vyas
Publisher : John Wiley & Sons
ISBN 13 : 1119761697
Total Pages : 276 pages
Book Rating : 4.1/5 (197 download)

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Book Synopsis Artificial Intelligence for Renewable Energy Systems by : Ajay Kumar Vyas

Download or read book Artificial Intelligence for Renewable Energy Systems written by Ajay Kumar Vyas and published by John Wiley & Sons. This book was released on 2022-03-02 with total page 276 pages. Available in PDF, EPUB and Kindle. Book excerpt: ARTIFICIAL INTELLIGENCE FOR RENEWABLE ENERGY SYSTEMS Renewable energy systems, including solar, wind, biodiesel, hybrid energy, and other relevant types, have numerous advantages compared to their conventional counterparts. This book presents the application of machine learning and deep learning techniques for renewable energy system modeling, forecasting, and optimization for efficient system design. Due to the importance of renewable energy in today’s world, this book was designed to enhance the reader’s knowledge based on current developments in the field. For instance, the extraction and selection of machine learning algorithms for renewable energy systems, forecasting of wind and solar radiation are featured in the book. Also highlighted are intelligent data, renewable energy informatics systems based on supervisory control and data acquisition (SCADA); and intelligent condition monitoring of solar and wind energy systems. Moreover, an AI-based system for real-time decision-making for renewable energy systems is presented; and also demonstrated is the prediction of energy consumption in green buildings using machine learning. The chapter authors also provide both experimental and real datasets with great potential in the renewable energy sector, which apply machine learning (ML) and deep learning (DL) algorithms that will be helpful for economic and environmental forecasting of the renewable energy business. Audience The primary target audience includes research scholars, industry engineers, and graduate students working in renewable energy, electrical engineering, machine learning, information & communication technology.

Preventive Maintenance and Fault Detection for Wind Turbine Generators Using a Statistical Model

Author : Ian Kuiler
Publisher :
ISBN 13 :
Total Pages : pages
Book Rating : 4.:/5 (115 download)

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Book Synopsis Preventive Maintenance and Fault Detection for Wind Turbine Generators Using a Statistical Model by : Ian Kuiler

Download or read book Preventive Maintenance and Fault Detection for Wind Turbine Generators Using a Statistical Model written by Ian Kuiler and published by . This book was released on 2018 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: Vigilant fault diagnosis and preventive maintenance has the potential to significantly decrease costs associated with wind generators. As wind energy continues the upward growth in technology and continued worldwide adoption and implementation, the application of fault diagnosis techniques will become more imperative. Fault diagnosis and preventive maintenance techniques for wind turbine generators are still at an early stage compared to matured strategies used for generators in conventional power plants. The cost of wind energy can be further reduced if failures are predicted in advance of a major structural failure, which leads to less unplanned maintenance. High maintenance cost of wind turbines means that predictive strategies like fault diagnosis and preventive maintenance techniques are necessary to manage life cycle costs of critical components. Squirrel-Cage Induction Generators (SCIG) are the prevailing generator type and are more robust and cheaper to manufacturer compared to other generator types used in wind turbines. A statistical model was developed using SCADA data to estimate the relationships between winding temperatures and other variables. Predicting faults in stator windings are challenging because the unhealthy condition rapidly evolves into a functional failure.

2021 Australian & New Zealand Control Conference (ANZCC).

Author :
Publisher :
ISBN 13 : 9781665416504
Total Pages : pages
Book Rating : 4.4/5 (165 download)

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Book Synopsis 2021 Australian & New Zealand Control Conference (ANZCC). by :

Download or read book 2021 Australian & New Zealand Control Conference (ANZCC). written by and published by . This book was released on 2021 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt:

AI Approaches to Smart and Sustainable Power Systems

Author : Ashok Kumar, L.
Publisher : IGI Global
ISBN 13 :
Total Pages : 455 pages
Book Rating : 4.3/5 (693 download)

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Book Synopsis AI Approaches to Smart and Sustainable Power Systems by : Ashok Kumar, L.

Download or read book AI Approaches to Smart and Sustainable Power Systems written by Ashok Kumar, L. and published by IGI Global. This book was released on 2024-03-25 with total page 455 pages. Available in PDF, EPUB and Kindle. Book excerpt: Today, the global power demand relies on a delicate balance between conventional and renewable energy systems, necessitating both efficient power generation and the effective utilization of these energy resources through appropriate energy storage solutions. Integrating microgrid systems into the utility grid has become a critical facet of modern power systems. The intermittent and unpredictable nature of these energy sources poses a formidable challenge for academic scholars and researchers. This compels them to explore under-investigated areas, including energy source estimation, storage elements, load pattern prediction, coordination among distributed sources, and the development of energy management algorithms for precise and efficient control. AI Approaches to Smart and Sustainable Power Systems tackles these issues using cutting-edge AI techniques. It examines the most effective methods to optimize voltage, frequency, power, fault diagnosis, component health, and overall power system quality and reliability. AI empowers predictive and preventive maintenance for a sustainable energy future. The book focuses on emerging research areas, including renewable energy, power flow calculations, demand scheduling, real-time performance validation, and AI integration into modern power systems, accompanied by insightful case studies.

Artificial Intelligence and Machine Learning in the Thermal Spray Industry

Author : Lalit Thakur
Publisher : CRC Press
ISBN 13 : 1000996212
Total Pages : 139 pages
Book Rating : 4.0/5 (9 download)

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Book Synopsis Artificial Intelligence and Machine Learning in the Thermal Spray Industry by : Lalit Thakur

Download or read book Artificial Intelligence and Machine Learning in the Thermal Spray Industry written by Lalit Thakur and published by CRC Press. This book was released on 2023-12-01 with total page 139 pages. Available in PDF, EPUB and Kindle. Book excerpt: · Highlights how Artificial Intelligence and Machine Learning techniques are used in the Thermal Spray industry to predict future research directions · Sheds light on Artificial Intelligence’s versatility, revealing its applicability in solving problems related to conventional simulation and numeric modeling techniques · Combines automated technologies with expert machines to show several advantages, including decreased error and greater accuracy in judgment, and prediction, enhanced efficiency, reduced time consumed, and lower costs · Discusses how certain barriers are preventing the successfully implementing of Artificial Intelligence in the Thermal Spray industry Looks at how training and validating more models with microstructural features of deposited coating will be the center point to grooming this technology in the future · Offers a thorough analysis of the digital technologies available for modeling and achieving high-performance coatings including giving Artificial intelligence-related models like ANN and CNN more attention

AI-Driven IoT Systems for Industry 4.0

Author : Deepa Jose
Publisher : CRC Press
ISBN 13 : 1040041159
Total Pages : 419 pages
Book Rating : 4.0/5 (4 download)

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Book Synopsis AI-Driven IoT Systems for Industry 4.0 by : Deepa Jose

Download or read book AI-Driven IoT Systems for Industry 4.0 written by Deepa Jose and published by CRC Press. This book was released on 2024-07-30 with total page 419 pages. Available in PDF, EPUB and Kindle. Book excerpt: The purpose of this book is to discuss the trends and key drivers of Internet of Things (IoT) and artificial intelligence (AI) for automation in Industry 4.0. IoT and AI are transforming the industry thus accelerating efficiency and forging a more reliable automated enterprise. AI-driven IoT systems for Industry 4.0 explore current research to be carried out in the cutting-edge areas of AI for advanced analytics, integration of industrial IoT (IIoT) solutions and Edge components, automation in cyber-physical systems, world leading Industry 4.0 frameworks and adaptive supply chains, etc. A thorough exploration of Industry 4.0 is provided, focusing on the challenges of digital transformation and automation. It covers digital connectivity, sensors, and the integration of intelligent thinking and data science. Emphasizing the significance of AI, the chapter delves into optimal decision-making in Industry 4.0. It extensively examines automation and hybrid edge computing architecture, highlighting their applications. The narrative then shifts to IIoT and edge AI, exploring their convergence and the use of edge AI for visual insights in smart factories. The book concludes by discussing the role of AI in constructing digital twins, speeding up product development lifecycles, and offering insights for decision-making in smart factories. Throughout, the emphasis remains on the transformative impact of deep learning and AI in automating and accelerating manufacturing processes within the context of Industry 4.0. This book is intended for undergraduates, postgraduates, academicians, researchers, and industry professionals in industrial and computer engineering.

Artificial Intelligence of Things for Achieving Sustainable Development Goals

Author : Sanjay Misra
Publisher : Springer Nature
ISBN 13 : 3031534336
Total Pages : 394 pages
Book Rating : 4.0/5 (315 download)

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Book Synopsis Artificial Intelligence of Things for Achieving Sustainable Development Goals by : Sanjay Misra

Download or read book Artificial Intelligence of Things for Achieving Sustainable Development Goals written by Sanjay Misra and published by Springer Nature. This book was released on with total page 394 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Wireless Health Monitoring and Improvement System for Wind Turbines

Author : Suratsavadee Koonlaboon Korkua
Publisher :
ISBN 13 :
Total Pages : pages
Book Rating : 4.:/5 (794 download)

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Book Synopsis Wireless Health Monitoring and Improvement System for Wind Turbines by : Suratsavadee Koonlaboon Korkua

Download or read book Wireless Health Monitoring and Improvement System for Wind Turbines written by Suratsavadee Koonlaboon Korkua and published by . This book was released on 2011 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: Wind power has become the world's fastest growing renewable energy resource. The world-wide wind power installed capacity has exceeded 120 GW. The United States has set a target of 20% wind-based electricity generation, over 300 GW, by 2030. As wind power is growing towards becoming a major utility source, it is urgent to guarantee the reliable operation of wind power systems. To avoid unexpected equipment failures, the focus in most wind farm is shifting from scheduled preventive maintenance to predictive maintenance. Predictive maintenance by condition-based monitoring of electrical machines is a scientific approach that is becoming a new strategy for maintenance management. Vibration analysis is also a measurement tool used to identify, predict, and prevent failures in rotating machinery. Implementing vibration analysis will improve the reliability of the machine and lead to better machine efficiency, reducing downtime by eliminating unexpected mechanical or electrical failures. Traditionally, monitoring systems are implemented as in wired systems formed by communication cables and various types of sensors. The cost of installation and maintenance such a system is more expensive than the cost of the sensors themselves. To overcome the restrictions of wired networks, using wireless system for monitoring is proposed. A wireless sensor network is a new control network that integrates the sensors, and embedded computer, wireless communication, and intelligent processing technology. ZigBee is a new wireless networking technology with low power, low cost, and short time-delay characteristics. Compared with other similar standards such as Bluetooth, it tends to provide each single device lower complexity and cost. Based on ZigBee network communication technology, the system can deal with the various operating parameters of remote transmission, real-time data collection, and real-time health monitoring systems. Moreover, ZigBee wireless technology enables the identification of the location of each node under the network with several types of positioning algorithms. This study presents and develops a ZigBee based wireless sensor network for machine health monitoring of induction machines. The three-axis vibration signals obtained from the monitoring system are then processed and analyzed with signal processing techniques. The vibration detection techniques with suitably modified algorithms are used to extract information for an induction machine health diagnostic. The severity level of abnormality and the remaining usable life are also explored. The goal for this research is not only to monitor the machine health of wind turbine system, but also to develop a control method for doubly-fed induction generators (DFIG) that addresses the issues associated to the rotor imbalance condition of the generator. Rotor imbalance is a mechanical disturbance related problem. It is a condition where there is more weight distributed on one side of a rotating part of the rotor than on the other side. It might be caused by wind wheel unbalances, shaft imbalances, or mechanical looseness. This kind of event will directly cause oscillation on the output signal of the generator such as generated output power, current, and voltage. The proposed control method will improve the performance of the DFIG control system by reducing the oscillation of the generator output and allowing the system to operate during the slightly unbalanced condition. To suppress the vibration and minimize the oscillation of the generated output, in addition to reducing the stresses on the wind turbine, the rotor side inverter controller is designed and tested by way of a digital simulation on the Matlab/Simulink platform. The wireless health monitoring system for wind turbine based on vibration detection shows the validity and distinct advantages in such a condition based monitoring system. The severity level of rotor imbalance is successfully estimated by using machine vibration analysis. Moreover, the systematic control design of the proposed vibration suppression by means of a rotor side inverter controller is explored and discussed. The real wind speed data of four different cases from the ERCOT system were used as input to test the performance and capabilities of the control scheme. The simulation results of the generator output show the effectiveness of this proposed rotor side inverter controller. It effectively reduces the oscillation of power, current, and torque output of the DFIG wind turbine.

Maintenance, Replacement, and Reliability

Author : Andrew K. S. Jardine
Publisher : CRC Press
ISBN 13 : 042966446X
Total Pages : 419 pages
Book Rating : 4.4/5 (296 download)

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Book Synopsis Maintenance, Replacement, and Reliability by : Andrew K. S. Jardine

Download or read book Maintenance, Replacement, and Reliability written by Andrew K. S. Jardine and published by CRC Press. This book was released on 2021-09-15 with total page 419 pages. Available in PDF, EPUB and Kindle. Book excerpt: Since the publication of the second edition in 2013, there has been an increasing interest in asset management globally, as evidenced by a series of international standards on asset management systems, to achieve excellence in asset management. This cannot be achieved without high-quality data and the tools for data interpretation. The importance of such requirements is widely recognized by industry. The third edition of this textbook focuses on tools for physical asset management decisions that are data driven. It also uses a theoretical foundation to the tools (mathematical models) that can be used to optimize a variety of key maintenance/replacement/reliability decisions. Problem sets with answers are provided at the end of each chapter. Also available is an extensive set of PowerPoint slides and a solutions manual upon request with qualified textbook adoptions. This new edition can be used in undergraduate or post-graduate courses on physical asset management.