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Investigation Of Model Based Sensor Fault Detection For Wind Turbines Using A Single Sensor
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Book Synopsis Investigation of Model-based Sensor Fault Detection for Wind Turbines Using a Single Sensor by : Fatima Azzahra El Azzouzi
Download or read book Investigation of Model-based Sensor Fault Detection for Wind Turbines Using a Single Sensor written by Fatima Azzahra El Azzouzi and published by . This book was released on 2012 with total page 74 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Fault Detection and Isolation of Wind Turbines Using Immune System Inspired Algorithms by : Esmaeil AliZadeh
Download or read book Fault Detection and Isolation of Wind Turbines Using Immune System Inspired Algorithms written by Esmaeil AliZadeh and published by . This book was released on 2017 with total page 166 pages. Available in PDF, EPUB and Kindle. Book excerpt: Recently, the research focus on renewable sources of energy has been growing intensively. This is mainly due to potential depletion of fossil fuels and its associated environmental concerns, such as pollution and greenhouse gas emissions. Wind energy is one of the fastest growing sources of renewable energy, and policy makers in both developing and developed countries have built their vision on future energy supply based on and by emphasizing the wind power. The increase in the number of wind turbines, as well as their size, have led to undeniable care and attention to health and condition monitoring as well as fault diagnosis of wind turbine systems and their components.In this thesis, two main immune inspired algorithms are used to perform Fault Detection and Isolation (FDI) of a Wind Turbine (WT), namely the Negative Selection Algorithm (NSA) as well as the Dendritic Cell Algorithm (DCA).First, an NSA-based fault diagnosis methodology is proposed in which a hierarchical bank of NSAs is used to detect and isolate both individual as well as simultaneously occurring faults common to the wind turbines. A smoothing moving window filter is then utilized to further improve the reliability and performance of the proposed FDI scheme. Moreover, the performance of the proposed scheme is compared with the state-of-the-art data-driven technique, namely Support Vector Machine (SVM) to demonstrate and illustrate the superiority and advantages of the proposed NSA-based FDI scheme. Finally, a nonparametric statistical comparison test is implemented to evaluate the proposed methodology with that of the SVM under various fault severities.In the second part, another immune inspired methodology, namely the Dendritic Cell Algorithm (DCA) is used to perform online sensor fault FDI. A noise filter is also designed to attenuate the measurement noise, resulting in better FDI results. The proposed DCA-based FDI scheme is then compared with the previously developed NSA-based FDI scheme, and a nonparametric statistical comparison test is also performed.Both of the proposed immune inspired frameworks are applied to a well-known wind turbine benchmark model in order to validate the effectiveness of the proposed methodologies.
Book Synopsis Model-Based Fault Diagnosis by : Zhenhua Wang
Download or read book Model-Based Fault Diagnosis written by Zhenhua Wang and published by Springer Nature. This book was released on 2022-10-28 with total page 207 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book investigates in detail model-based fault diagnosis methods, including observer-based residual generation, residual evaluation based on threshold computation, observer-based fault isolation strategies, observer-based fault estimation, Kalman filter-based fault diagnosis methods, and parity space approach. Studies on model-based fault diagnosis have attracted engineers and scientists from various disciplines, such as electrical, aerospace, mechanical, and chemical engineering. Pursuing a holistic approach, the book establishes a fundamental framework for this topic, while emphasizing the importance of state-space approach. The methods introduced in the book are systemic and easy to follow. The book is intended for undergraduate and graduate students who are interested in fault diagnosis and state estimation, researchers investigating fault diagnosis and fault-tolerant control, and control system design engineers working on safety-critical systems.
Book Synopsis Fault Diagnosis and Sustainable Control of Wind Turbines by : Silvio Simani
Download or read book Fault Diagnosis and Sustainable Control of Wind Turbines written by Silvio Simani and published by Butterworth-Heinemann. This book was released on 2018-01-02 with total page 230 pages. Available in PDF, EPUB and Kindle. Book excerpt: Fault Diagnosis and Sustainable Control of Wind Turbines: Robust Data-Driven and Model-Based Strategies discusses the development of reliable and robust fault diagnosis and fault-tolerant (‘sustainable’) control schemes by means of data-driven and model-based approaches. These strategies are able to cope with unknown nonlinear systems and noisy measurements. The book also discusses simpler solutions relying on data-driven and model-based methodologies, which are key when on-line implementations are considered for the proposed schemes. The book targets both professional engineers working in industry and researchers in academic and scientific institutions. In order to improve the safety, reliability and efficiency of wind turbine systems, thus avoiding expensive unplanned maintenance, the accommodation of faults in their early occurrence is fundamental. To highlight the potential of the proposed methods in real applications, hardware–in–the–loop test facilities (representing realistic wind turbine systems) are considered to analyze the digital implementation of the designed solutions. The achieved results show that the developed schemes are able to maintain the desired performances, thus validating their reliability and viability in real-time implementations. Different groups of readers—ranging from industrial engineers wishing to gain insight into the applications' potential of new fault diagnosis and sustainable control methods, to the academic control community looking for new problems to tackle—will find much to learn from this work. Provides wind turbine models with varying complexity, as well as the solutions proposed and developed by the authors Addresses in detail the design, development and realistic implementation of fault diagnosis and fault tolerant control strategies for wind turbine systems Addresses the development of sustainable control solutions that, in general, do not require the introduction of further or redundant measurements Proposes active fault tolerant ('sustainable') solutions that are able to maintain the wind turbine working conditions with gracefully degraded performance before required maintenance can occur Presents full coverage of the diagnosis and fault tolerant control problem, starting from the modeling and identification and finishing with diagnosis and fault tolerant control approaches Provides MATLAB and Simulink codes for the solutions proposed
Book Synopsis Prognostics and Health Aware Model Predictive Control of Wind Turbines by : Héctor Eloy Sánchez Sardi
Download or read book Prognostics and Health Aware Model Predictive Control of Wind Turbines written by Héctor Eloy Sánchez Sardi and published by . This book was released on 2017 with total page 147 pages. Available in PDF, EPUB and Kindle. Book excerpt: Wind turbines components are subject to considerable stresses and fatigue due to extreme environmental conditions to which they are exposed, especially those located offshore. Also, the most common faults present in wind turbine components have been investigated for years by the research community and that has led to propose a fault diagnosis and fault tolerant control wind turbine benchmark which include a set of faults that affect the sensors and actuators of several wind turbine components. This thesis presents some contributions to the fields of fault diagnosis, fault-tolerant control, prognostics and its integration with wind turbine control which leads to proposing a control approach called health-aware model predictive control (HAMPC). The contributions are summarized below: - Model-based fault diagnosis: to perform fault detection and isolation interval-based observers together with a set of analytical redundant relations (ARRs) are obtained based on a structural analysis and the fault signature matrix that relates the ARRs with the faults. Fault tolerant control: it is proposed a fault tolerant control scheme that integrates fault detection and an algorithm for fault accommodation. The scheme has the objective to avoid the increment of blades and tower loads when a fault in the rotor azimuth angle sensor occurs using the individual pitch control technique (IPC). Wind turbine blades fatigue prognostics and degradation: fatigue is assessed using the rainflow counting algorithm which is used to estimate the accumulated damage and for degradation, it is used a stiffness degradation model of blades material which is used to make predictions of remaining useful life (RUL). Wind turbines health control: the module for the health of the system based on fatigue damage estimation and RUL predictions is integrated with model predictive control (MPC) leading to the proposed control approach (HAMPC). The contributions presented in this thesis have been validated on a wind turbine study case that uses a 5MW wind turbine reference model implemented in a high fidelity wind turbine simulator (FAST).
Book Synopsis Fault Detection and Diagnosis by : Constantin Volosencu
Download or read book Fault Detection and Diagnosis written by Constantin Volosencu and published by . This book was released on 2018 with total page 128 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book offers a selection of papers in the field of fault detection and diagnosis, promoting new research results in the field, which come to join other publications in the literature. Authors from countries of four continents: United States of America, South Africa, China, India, Algeria and Croatia published worked examples and case studies resulting from their research in the field. Fault detection and diagnosis has a great importance in all industrial processes, to assure the monitoring, maintenance and repair of the complex processes, including all hardware, firmware and software. The book has four sections, determined by the application domain and the methods used: 1. Hybrid Computing Systems, 2. Power Systems, 3. Power Electronics and 4. Kalman Filtering. In the first section, the readers will find a technical report on fault diagnosis of hybrid computing systems, based on the chaotic-map method that uses the exponential divergence and wide Fourier properties of the trajectories, combined with memory allocations and assignments. In the second section, two chapters are included: one of them presents a study on preventive maintenance and fault detection for wind turbine generators using statistical models and the second chapter presents a technical report on fault diagnosis for turbo-generators, based on the mechanical-electrical intersectional characteristics. The third section contains a technical report that presents some techniques of detection and localization of open-circuit faults in a three-phase voltage source inverter fed induction motor. The fourth section presents a theoretical study on the application of distributed discrete-time linear Kalman filtering with decentralized structure of sensors in fault residual generation.
Book Synopsis Fault Detection and Flight Data Measurement by : Ihab Samy
Download or read book Fault Detection and Flight Data Measurement written by Ihab Samy and published by Springer. This book was released on 2012-02-02 with total page 185 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book considers two popular topics: fault detection and isolation (FDI) and flight data estimation using flush air data sensing (FADS) systems. Literature surveys, comparison tests, simulations and wind tunnel tests are performed. In both cases, a UAV platform is considered for demonstration purposes. In the first part of the book, FDI is considered for sensor faults where a neural network approach is implemented. FDI is applied both in academia and industry resulting in many publications over the past 50 years or so. However few publications consider neural networks in comparison to traditional techniques such as observer based, parameter estimations and parity space approaches. The second part of this book focuses on how to estimate flight data (angle of attack, airspeed) using a matrix of pressure sensors and a neural network model. In conclusion this book can serve as an introduction to FDI and FADS systems, a literature survey, and a case study for UAV applications.
Book Synopsis Data-Driven and Model-Based Methods for Fault Detection and Diagnosis by : Majdi Mansouri
Download or read book Data-Driven and Model-Based Methods for Fault Detection and Diagnosis written by Majdi Mansouri and published by Elsevier. This book was released on 2020-02-05 with total page 322 pages. Available in PDF, EPUB and Kindle. Book excerpt: Data-Driven and Model-Based Methods for Fault Detection and Diagnosis covers techniques that improve the quality of fault detection and enhance monitoring through chemical and environmental processes. The book provides both the theoretical framework and technical solutions. It starts with a review of relevant literature, proceeds with a detailed description of developed methodologies, and then discusses the results of developed methodologies, and ends with major conclusions reached from the analysis of simulation and experimental studies. The book is an indispensable resource for researchers in academia and industry and practitioners working in chemical and environmental engineering to do their work safely. Outlines latent variable based hypothesis testing fault detection techniques to enhance monitoring processes represented by linear or nonlinear input-space models (such as PCA) or input-output models (such as PLS) Explains multiscale latent variable based hypothesis testing fault detection techniques using multiscale representation to help deal with uncertainty in the data and minimize its effect on fault detection Includes interval PCA (IPCA) and interval PLS (IPLS) fault detection methods to enhance the quality of fault detection Provides model-based detection techniques for the improvement of monitoring processes using state estimation-based fault detection approaches Demonstrates the effectiveness of the proposed strategies by conducting simulation and experimental studies on synthetic data
Book Synopsis Sensor Fault Diagnosis by : Vasso Reppa
Download or read book Sensor Fault Diagnosis written by Vasso Reppa and published by Now Publishers. This book was released on 2016-05-04 with total page 264 pages. Available in PDF, EPUB and Kindle. Book excerpt: Recent advances in information and communication technologies, embedded systems and sensor networks have generated significant research activity in the development of so-called cyber-physical systems. An example of a large network of cyber-physical systems is a smart city with intelligent infrastructures for supporting the environment, energy and water distribution, transportation, telecommunication, health care, home automation, and so on. From a systems point of view, safety, reliability and fault tolerance become key challenges in designing cyber-physical systems. One of the major issues is detecting and correcting faults in the sensors that form a critical part of these networks and systems. For example, if two sensors should provide similar information, how do you know which one is at fault should their readings suddenly greatly differ? Sensor Fault Diagnosis addresses all the issues in sensor fault detection and isolation. It provides a clear tutorial on the challenges and models that can be used to address them. It describes, in detail, the requirements for modeling the systems, designing the architecture, detecting faults, isolating those faults, and presents learning techniques for enhancing performance. This monograph will appeal to all researchers and students working on large sensor networks and systems.
Book Synopsis Sensor Signal and Information Processing II by : Wai Lok Woo
Download or read book Sensor Signal and Information Processing II written by Wai Lok Woo and published by MDPI. This book was released on 2020-12-29 with total page 418 pages. Available in PDF, EPUB and Kindle. Book excerpt: In the current age of information explosion, newly invented technological sensors and software are now tightly integrated with our everyday lives. Many sensor processing algorithms have incorporated some forms of computational intelligence as part of their core framework in problem solving. These algorithms have the capacity to generalize and discover knowledge for themselves and learn new information whenever unseen data are captured. The primary aim of sensor processing is to develop techniques to interpret, understand, and act on information contained in the data. The interest of this book is in developing intelligent signal processing in order to pave the way for smart sensors. This involves mathematical advancement of nonlinear signal processing theory and its applications that extend far beyond traditional techniques. It bridges the boundary between theory and application, developing novel theoretically inspired methodologies targeting both longstanding and emergent signal processing applications. The topic ranges from phishing detection to integration of terrestrial laser scanning, and from fault diagnosis to bio-inspiring filtering. The book will appeal to established practitioners, along with researchers and students in the emerging field of smart sensors processing.
Book Synopsis Sensor Fault Diagnosis Using Principal Component Analysis by : Mahmoudreza Sharifi
Download or read book Sensor Fault Diagnosis Using Principal Component Analysis written by Mahmoudreza Sharifi and published by . This book was released on 2010 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: The purpose of this research is to address the problem of fault diagnosis of sensors which measure a set of direct redundant variables. This study proposes: 1. A method for linear senor fault diagnosis 2. An analysis of isolability and detectability of sensor faults 3. A stochastic method for the decision process 4. A nonlinear approach to sensor fault diagnosis. In this study, first a geometrical approach to sensor fault detection is proposed. The sensor fault is isolated based on the direction of residuals found from a residual generator. This residual generator can be constructed from an input-output model in model based methods or from a Principal Component Analysis (PCA) based model in data driven methods. Using this residual generator and the assumption of white Gaussian noise, the effect of noise on the isolability is studied, and the minimum magnitude of isolable fault in each sensor is found based on the distribution of noise in the measurement system. Next, for the decision process a probabilistic approach to sensor fault diagnosis is presented. Unlike most existing probabilistic approaches to fault diagnosis, which are based on Bayesian Belief Networks, in this approach the probabilistic model is directly extracted from a parity equation. The relevant parity equation can be found using a model of the system or through PCA analysis of data measured from the system. In addition, a sensor detectability index is introduced that specifies the level of detectability of sensor faults in a set of redundant sensors. This index depends only on the internal relationships of the variables of the system and noise level. Finally, the proposed linear sensor fault diagnosis approach has been extended to nonlinear method by separating the space of measurements into several local linear regions. This classification has been performed by application of Mixture of Probabilistic PCA (MPPCA). The proposed linear and nonlinear methods are tested on three different systems. The linear method is applied to sensor fault diagnosis in a smart structure and to the Tennessee Eastman process model, and the nonlinear method is applied to a data set collected from a fully instrumented HVAC system.
Book Synopsis Fault Detection and Diagnosis in Industrial Systems by : L.H. Chiang
Download or read book Fault Detection and Diagnosis in Industrial Systems written by L.H. Chiang and published by Springer Science & Business Media. This book was released on 2012-12-06 with total page 281 pages. Available in PDF, EPUB and Kindle. Book excerpt: Early and accurate fault detection and diagnosis for modern chemical plants can minimize downtime, increase the safety of plant operations, and reduce manufacturing costs. This book presents the theoretical background and practical techniques for data-driven process monitoring. It demonstrates the application of all the data-driven process monitoring techniques to the Tennessee Eastman plant simulator, and looks at the strengths and weaknesses of each approach in detail. A plant simulator and problems allow readers to apply process monitoring techniques.
Book Synopsis A Model-based Sensor Fault Detection and Isolation Approach for Smooth Deterministic Nonlinear Dynamic Systems with Application by : Timothy Alan Himmelspach
Download or read book A Model-based Sensor Fault Detection and Isolation Approach for Smooth Deterministic Nonlinear Dynamic Systems with Application written by Timothy Alan Himmelspach and published by . This book was released on 1993 with total page 670 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Large Grid-Connected Wind Turbines by : Frede Blaabjerg
Download or read book Large Grid-Connected Wind Turbines written by Frede Blaabjerg and published by MDPI. This book was released on 2019-04-02 with total page 212 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book covers the technological progress and developments of a large-scale wind energy conversion system along with its future trends, with each chapter constituting a contribution by a different leader in the wind energy arena. Recent developments in wind energy conversion systems, system optimization, stability augmentation, power smoothing, and many other fascinating topics are included in this book. Chapters are supported through modeling, control, and simulation analysis. This book contains both technical and review articles.
Author :National Aeronautics and Space Adm Nasa Publisher :Independently Published ISBN 13 :9781794371316 Total Pages :30 pages Book Rating :4.3/5 (713 download)
Book Synopsis On Identifiability of Bias-Type Actuator-Sensor Faults in Multiple-Model-Based Fault Detection and Identification by : National Aeronautics and Space Adm Nasa
Download or read book On Identifiability of Bias-Type Actuator-Sensor Faults in Multiple-Model-Based Fault Detection and Identification written by National Aeronautics and Space Adm Nasa and published by Independently Published. This book was released on 2019-01-19 with total page 30 pages. Available in PDF, EPUB and Kindle. Book excerpt: This paper explores a class of multiple-model-based fault detection and identification (FDI) methods for bias-type faults in actuators and sensors. These methods employ banks of Kalman-Bucy filters to detect the faults, determine the fault pattern, and estimate the fault values, wherein each Kalman-Bucy filter is tuned to a different failure pattern. Necessary and sufficient conditions are presented for identifiability of actuator faults, sensor faults, and simultaneous actuator and sensor faults. It is shown that FDI of simultaneous actuator and sensor faults is not possible using these methods when all sensors have biases. Joshi, Suresh M. Langley Research Center NASA/TM-2012-217586, L-20149, NF1676L-14727
Book Synopsis Condition Monitoring and Nonlinear Frequency Analysis Based Fault Detection of Mechanical Vibration Systems by : Hogir Rafiq
Download or read book Condition Monitoring and Nonlinear Frequency Analysis Based Fault Detection of Mechanical Vibration Systems written by Hogir Rafiq and published by Springer Nature. This book was released on 2023-08-26 with total page 206 pages. Available in PDF, EPUB and Kindle. Book excerpt: Hogir Rafiq proposes two approaches, the signal processing based condition monitoring approaches with applications to fault detection in gear systems, and application of deep mathematical and system theoretical methods to fault detection. The author develops the multivariate empirical mode decomposition (MEMD) algorithm to enhance the capability of extracting fault features and theoretical problems in nonlinear frequency analysis methods, respectively. The effectiveness has been demonstrated by an experimental study on a wind turbine gearbox test rig.
Book Synopsis Model-based Sensor Fault Diagnosis in an Industrial Gas Engine Power Plant by : Stefan Jakubek
Download or read book Model-based Sensor Fault Diagnosis in an Industrial Gas Engine Power Plant written by Stefan Jakubek and published by . This book was released on 2000 with total page 206 pages. Available in PDF, EPUB and Kindle. Book excerpt:
