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Diagnostics and Prognostics of Engineering Systems: Methods and Techniques

Diagnostics and Prognostics of Engineering Systems: Methods and Techniques
Author: Kadry, Seifedine
Publisher: IGI Global
Total Pages: 461
Release: 2012-09-30
Genre: Technology & Engineering
ISBN: 146662096X
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Industrial Prognostics predicts an industrial system’s lifespan using probability measurements to determine the way a machine operates. Prognostics are essential in determining being able to predict and stop failures before they occur. Therefore the development of dependable prognostic procedures for engineering systems is important to increase the system’s performance and reliability. Diagnostics and Prognostics of Engineering Systems: Methods and Techniques provides widespread coverage and discussions on the methods and techniques of diagnosis and prognosis systems. Including practical examples to display the method’s effectiveness in real-world applications as well as the latest trends and research, this reference source aims to introduce fundamental theory and practice for system diagnosis and prognosis.

Fault Diagnosis and Prognosis Techniques for Complex Engineering Systems

Fault Diagnosis and Prognosis Techniques for Complex Engineering Systems
Author: Hamid Reza Karimi
Publisher: Academic Press
Total Pages: 421
Release: 2021-06-05
Genre: Technology & Engineering
ISBN: 0128224886
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Fault Diagnosis and Prognosis Techniques for Complex Engineering Systems gives a systematic description of the many facets of envisaging, designing, implementing, and experimentally exploring emerging trends in fault diagnosis and failure prognosis in mechanical, electrical, hydraulic and biomedical systems. The book is devoted to the development of mathematical methodologies for fault diagnosis and isolation, fault tolerant control, and failure prognosis problems of engineering systems. Sections present new techniques in reliability modeling, reliability analysis, reliability design, fault and failure detection, signal processing, and fault tolerant control of engineering systems. Sections focus on the development of mathematical methodologies for diagnosis and prognosis of faults or failures, providing a unified platform for understanding and applicability of advanced diagnosis and prognosis methodologies for improving reliability purposes in both theory and practice, such as vehicles, manufacturing systems, circuits, flights, biomedical systems. This book will be a valuable resource for different groups of readers – mechanical engineers working on vehicle systems, electrical engineers working on rotary machinery systems, control engineers working on fault detection systems, mathematicians and physician working on complex dynamics, and many more. Presents recent advances of theory, technological aspects, and applications of advanced diagnosis and prognosis methodologies in engineering applications Provides a series of the latest results, including fault detection, isolation, fault tolerant control, failure prognosis of components, and more Gives numerical and simulation results in each chapter to reflect engineering practices

Prognostics and Health Management of Engineering Systems

Prognostics and Health Management of Engineering Systems
Author: Nam-Ho Kim
Publisher: Springer
Total Pages: 355
Release: 2016-10-24
Genre: Technology & Engineering
ISBN: 3319447424
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This book introduces the methods for predicting the future behavior of a system’s health and the remaining useful life to determine an appropriate maintenance schedule. The authors introduce the history, industrial applications, algorithms, and benefits and challenges of PHM (Prognostics and Health Management) to help readers understand this highly interdisciplinary engineering approach that incorporates sensing technologies, physics of failure, machine learning, modern statistics, and reliability engineering. It is ideal for beginners because it introduces various prognostics algorithms and explains their attributes, pros and cons in terms of model definition, model parameter estimation, and ability to handle noise and bias in data, allowing readers to select the appropriate methods for their fields of application.Among the many topics discussed in-depth are:• Prognostics tutorials using least-squares• Bayesian inference and parameter estimation• Physics-based prognostics algorithms including nonlinear least squares, Bayesian method, and particle filter• Data-driven prognostics algorithms including Gaussian process regression and neural network• Comparison of different prognostics algorithms divThe authors also present several applications of prognostics in practical engineering systems, including wear in a revolute joint, fatigue crack growth in a panel, prognostics using accelerated life test data, fatigue damage in bearings, and more. Prognostics tutorials with a Matlab code using simple examples are provided, along with a companion website that presents Matlab programs for different algorithms as well as measurement data. Each chapter contains a comprehensive set of exercise problems, some of which require Matlab programs, making this an ideal book for graduate students in mechanical, civil, aerospace, electrical, and industrial engineering and engineering mechanics, as well as researchers and maintenance engineers in the above fields.

Machine Learning and Knowledge Discovery for Engineering Systems Health Management

Machine Learning and Knowledge Discovery for Engineering Systems Health Management
Author: Ashok N. Srivastava
Publisher: CRC Press
Total Pages: 489
Release: 2016-04-19
Genre: Computers
ISBN: 1439841799
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This volume presents state-of-the-art tools and techniques for automatically detecting, diagnosing, and predicting the effects of adverse events in an engineered system. It emphasizes the importance of these techniques in managing the intricate interactions within and between engineering systems to maintain a high degree of reliability. Reflecting the interdisciplinary nature of the field, the book explains how the fundamental algorithms and methods of both physics-based and data-driven approaches effectively address systems health management in application areas such as data centers, aircraft, and software systems.

Intelligent Fault Diagnosis and Prognosis for Engineering Systems

Intelligent Fault Diagnosis and Prognosis for Engineering Systems
Author: George Vachtsevanos
Publisher: Wiley
Total Pages: 0
Release: 2006-09-29
Genre: Technology & Engineering
ISBN: 9780471729990
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Expert guidance on theory and practice in condition-based intelligent machine fault diagnosis and failure prognosis Intelligent Fault Diagnosis and Prognosis for Engineering Systems gives a complete presentation of basic essentials of fault diagnosis and failure prognosis, and takes a look at the cutting-edge discipline of intelligent fault diagnosis and failure prognosis technologies for condition-based maintenance. It thoroughly details the interdisciplinary methods required to understand the physics of failure mechanisms in materials, structures, and rotating equipment, and also presents strategies to detect faults or incipient failures and predict the remaining useful life of failing components. Case studies are used throughout the book to illustrate enabling technologies. Intelligent Fault Diagnosis and Prognosis for Engineering Systems offers material in a holistic and integrated approach that addresses the various interdisciplinary components of the field--from electrical, mechanical, industrial, and computer engineering to business management. This invaluably helpful book: * Includes state-of-the-art algorithms, methodologies, and contributions from leading experts, including cost-benefit analysis tools and performance assessment techniques * Covers theory and practice in a way that is rooted in industry research and experience * Presents the only systematic, holistic approach to a strongly interdisciplinary topic

Prognostics and Health Management of Electronics

Prognostics and Health Management of Electronics
Author: Michael G. Pecht
Publisher: John Wiley & Sons
Total Pages: 809
Release: 2018-08-15
Genre: Technology & Engineering
ISBN: 1119515300
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An indispensable guide for engineers and data scientists in design, testing, operation, manufacturing, and maintenance A road map to the current challenges and available opportunities for the research and development of Prognostics and Health Management (PHM), this important work covers all areas of electronics and explains how to: assess methods for damage estimation of components and systems due to field loading conditions assess the cost and benefits of prognostic implementations develop novel methods for in situ monitoring of products and systems in actual life-cycle conditions enable condition-based (predictive) maintenance increase system availability through an extension of maintenance cycles and/or timely repair actions; obtain knowledge of load history for future design, qualification, and root cause analysis reduce the occurrence of no fault found (NFF) subtract life-cycle costs of equipment from reduction in inspection costs, downtime, and inventory Prognostics and Health Management of Electronics also explains how to understand statistical techniques and machine learning methods used for diagnostics and prognostics. Using this valuable resource, electrical engineers, data scientists, and design engineers will be able to fully grasp the synergy between IoT, machine learning, and risk assessment.

Intelligent Prognostics for Engineering Systems with Machine Learning Techniques

Intelligent Prognostics for Engineering Systems with Machine Learning Techniques
Author: Gunjan Soni
Publisher: CRC Press
Total Pages: 261
Release: 2023-09-22
Genre: Technology & Engineering
ISBN: 1000954080
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The text discusses the latest data-driven, physics-based, and hybrid approaches employed in each stage of industrial prognostics and reliability estimation. It will be a useful text for senior undergraduate, graduate students, and academic researchers in areas such as industrial and production engineering, electrical engineering, and computer science. The book Discusses basic as well as advance research in the field of prognostics Explores integration of data collection, fault detection, degradation modeling and reliability prediction in one volume Covers prognostics and health management (PHM) of engineering systems Discusses latest approaches in the field of prognostics based on machine learning The text deals with tools and techniques used to predict/ extrapolate/ forecast the process behavior, based on current health state assessment and future operating conditions with the help of Machine learning. It will serve as a useful reference text for senior undergraduate, graduate students, and academic researchers in areas such as industrial and production engineering, manufacturing science, electrical engineering, and computer science.

Fault Detection, Diagnosis and Prognosis

Fault Detection, Diagnosis and Prognosis
Author: Fausto Pedro García Márquez
Publisher: BoD – Books on Demand
Total Pages: 177
Release: 2020-02-05
Genre: Mathematics
ISBN: 1789842131
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This book presents the main concepts, state of the art, advances, and case studies of fault detection, diagnosis, and prognosis. This topic is a critical variable in industry to reach and maintain competitiveness. Therefore, proper management of the corrective, predictive, and preventive politics in any industry is required. This book complements other subdisciplines such as economics, finance, marketing, decision and risk analysis, engineering, etc. The book presents real case studies in multiple disciplines. It considers the main topics using prognostic and subdiscipline techniques. It is essential to link these topics with the areas of finance, scheduling, resources, downtime, etc. to increase productivity, profitability, maintainability, reliability, safety, and availability, and reduce costs and downtime. Advances in mathematics, modeling, computational techniques, dynamic analysis, etc. are employed analytically. Computational techniques, dynamic analysis, probabilistic methods, and mathematical optimization techniques are expertly blended to support the analysis of prognostic problems with defined constraints and requirements. The book is intended for graduate students and professionals in industrial engineering, business administration, industrial organization, operations management, applied microeconomics, and the decisions sciences, either studying maintenance or needing to solve large, specific, and complex maintenance management problems as part of their jobs. The work will also be of interest to researches from academia.

Human Systems Engineering and Design

Human Systems Engineering and Design
Author: Tareq Ahram
Publisher: Springer
Total Pages: 1152
Release: 2018-10-16
Genre: Technology & Engineering
ISBN: 3030020533
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This book focuses on novel design and systems engineering approaches, including theories and best practices, for promoting a better integration of people and engineering systems. It covers a range of hot topics related to: development of activity-centered and user-centered systems; interface design and human-computer interaction; usability and user experience; cooperative, participatory and contextual models; emergent properties of human behavior; innovative materials in manufacturing, and many more. Particular emphasis is placed on applications in sports, healthcare, and medicine. The book, which gathers selected papers presented at the 1st International Conference on Human Systems Engineering and Design: Future Trends and Applications (IHSED 2018), held on October 25-27, 2018, at CHU-Université de Reims Champagne-Ardenne, France, provides researchers, practitioners and program managers with a snapshot of the state-of-the-art and current challenges in the field of human systems engineering and design.

Diagnostics and Prognostics

Diagnostics and Prognostics
Author: Jian Qu
Publisher: LAP Lambert Academic Publishing
Total Pages: 164
Release: 2012-04
Genre:
ISBN: 9783847307433
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In recent decades, condition-based maintenance (CBM) is acknowledged a cost-effective and widely used maintenance program for engineering systems. Diagnostics and prognostics are critical components of CBM responsible for offering information about present and future system conditions. These two components are respectively an integrated process covering several aspects that are essential for successful implementations of diagnostics and prognostics. For diagnostics, data to be used should be clean and useful. Data cleaning can provide clean data by removing outliers caused by noise, while feature selection can select useful characteristic features for fault classification. For prognostics, noise may appear in condition indicator values. Using such noisy values may result in unreliable predictions for prognostics. A method is thus demanded to provide predictions without noise effects. Support vector machine (SVM), a machine learning method, is recognized having good generalization ability and an effective tool for classification and prediction needed by diagnostics and prognostics. This book explores the potentials of SVM for addressing above problems in diagnostics and prognostics.