Download or read book Intelligent Prognostics for Engineering Systems with Machine Learning Techniques written by Gunjan Soni and published by CRC Press. This book was released on 2023-09-19 with total page 252 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.
Download or read book Intelligent Prognostics for Engineering Systems with Machine Learning Techniques written by Gunjan Soni and published by CRC Press. This book was released on 2023-09-22 with total page 261 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.
Download or read book Diagnostics and Prognostics of Engineering Systems Methods and Techniques written by Kadry, Seifedine and published by IGI Global. This book was released on 2012-09-30 with total page 461 pages. Available in PDF, EPUB and Kindle. Book excerpt: Industrial Prognostics predicts an industrial systems 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 systems 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 methods 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.
Download or read book Machine Learning and Knowledge Discovery for Engineering Systems Health Management written by Ashok N. Srivastava and published by CRC Press. This book was released on 2016-04-19 with total page 489 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.
Download or read book Intelligent Fault Diagnosis and Prognosis for Engineering Systems written by George Vachtsevanos and published by Wiley. This book was released on 2006-09-29 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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
Download or read book Data driven Diagnostics and Prognostics for Complex Systems written by Junchuan Shi and published by . This book was released on 2022 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: Recent advances in artificial intelligence or machine learning have the potential to significantly improve the effectiveness and efficiency of diagnostic and prognostic techniques. The objective of this research is to develop novel data-driven predictive models with machine learning and deep learning algorithms that allow one to model the degradation, detect the faults, as well as predict the remaining useful life (RUL) of complex systems, including bearings, gearboxes, and Lithium-ion (Li-ion) batteries. First, an enhanced ensemble learning algorithm is developed to improve the accuracy of RUL prediction by selecting diverse base learners and features at different degradation stages. The proposed method with increased diversity in base learners and features was demonstrated to be more accurate than other reported algorithms. Second, a convolutional long short-term memory (Conv-LSTM) approach is introduced to accurately classify the type, position, and direction of gear faults under different operating conditions by extracting spatiotemporal features from multiple sensors. The proposed method achieved 95% classification accuracy of fault type and 80% classification accuracy of fault location. Third, a deep learning method that combines convolutional neural networks (CNN) and bi-directional long short-term memory (BiLSTM) is developed to predict the discharge capacity and the end-of-discharge (EOD) of Li-ion batteries. The results show that by considering the discharge capacity estimated by CNN, the MAPE of EOD prediction using BiLSTM decreased from 8.52% to 3.21%. Fourth, a physics-informed machine learning method that combines the calendar and cycle aging (CCA) model and a LSTM model is developed to predict battery degradation behavior and RUL under different working conditions. The results show that the proposed method can predict the RUL of batteries accurately (10% in term of MAPE).
Download or read book Prognostics and Health Management of Electronics written by Michael G. Pecht and published by John Wiley & Sons. This book was released on 2008-09-11 with total page 335 pages. Available in PDF, EPUB and Kindle. Book excerpt: The first book on Prognostics and Health Management of Electronics Recently, the field of prognostics for electronic products has received increased attention due to the potential to provide early warning of system failures, forecast maintenance as needed, and reduce life cycle costs. In response to the subject's growing interest among industry, government, and academic professionals, this book provides a road map to the current challenges and opportunities for research and development in Prognostics and Health Management (PHM). The book begins with a review of PHM and the techniques being developed to enable a prognostics approach for electronic products and systems. building on this foundation, the book then presents the state of the art in sensor systems for in-situ health and usage monitoring. Next, it discusses the various models and algorithms that can be utilized in PHM. Finally, it concludes with a discussion of the opportunities in future research. Readers can use the information in this book to: Detect and isolate faults Reduce the occurrence of No Fault Found (NFF) Provide advanced warning of system failures Enable condition-based (predictive) maintenance Obtain knowledge of load history for future design, qualification, and root cause analysis Increase system availability through an extension of maintenance cycles and/or timely repair actions Subtract life cycle costs of equipment from reduction in inspection costs, down time, and inventory Prognostics and Health Management of Electronics is an indispensable reference for electrical engineers in manufacturing, systems maintenance, and management, as well as design engineers in all areas of electronics.
Download or read book Prognostics and Health Management of Engineering Systems written by Nam-Ho Kim and published by Springer. This book was released on 2016-10-24 with total page 355 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.
Download or read book Fault Diagnosis and Prognosis Techniques for Complex Engineering Systems written by Hamid Reza Karimi and published by Elsevier. This book was released on 2021-06-14 with total page 419 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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
Download or read book Advances in Data Driven Computing and Intelligent Systems written by Swagatam Das and published by Springer Nature. This book was released on 2023-09-04 with total page 885 pages. Available in PDF, EPUB and Kindle. Book excerpt: The volume is a collection of best selected research papers presented at International Conference on Advances in Data-driven Computing and Intelligent Systems (ADCIS 2022) held at BITS Pilani, K K Birla Goa Campus, Goa, India during 23 – 25 September 2022. It includes state-of-the art research work in the cutting-edge technologies in the field of data science and intelligent systems. The book presents data-driven computing; it is a new field of computational analysis which uses provided data to directly produce predictive outcomes. The book will be useful for academicians, research scholars, and industry persons.
Download or read book AI Techniques for Reliability Prediction for Electronic Components written by Bhargava, Cherry and published by IGI Global. This book was released on 2019-12-06 with total page 330 pages. Available in PDF, EPUB and Kindle. Book excerpt: In the industry of manufacturing and design, one major constraint has been enhancing operating performance using less time. As technology continues to advance, manufacturers are looking for better methods in predicting the condition and residual lifetime of electronic devices in order to save repair costs and their reputation. Intelligent systems are a solution for predicting the reliability of these components; however, there is a lack of research on the advancements of this smart technology within the manufacturing industry. AI Techniques for Reliability Prediction for Electronic Components provides emerging research exploring the theoretical and practical aspects of prediction methods using artificial intelligence and machine learning in the manufacturing field. Featuring coverage on a broad range of topics such as data collection, fault tolerance, and health prognostics, this book is ideally designed for reliability engineers, electronic engineers, researchers, scientists, students, and faculty members seeking current research on the advancement of reliability analysis using AI.
Download or read book Business Information Systems written by Witold Abramowicz and published by Springer. This book was released on 2018-07-11 with total page 426 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes the proceedings of the 21st International Conference on Business Information Systems, BIS 2018, held in Berlin, Germany, in July 2018. The BIS conference follows popular research trends, both in the academic and the business domain. Thus the theme of BIS 2018 was "Digital Transformation - An Imperative in Today's Business Markets". The 30 papers presented in this volume were carefully reviewed and selected from 96 submissions. They were organized in topical sections named: big and smart data and artificial intelligence; business and enterprise modeling; ICT project management; process management; smart infrastructures; social media and Web-based business information systems; applications, evaluations, and experiences.
Download or read book Modern Advances in Applied Intelligence written by Moonis Ali and published by Springer. This book was released on 2014-05-20 with total page 547 pages. Available in PDF, EPUB and Kindle. Book excerpt: The two volume set LNAI 8481 and 8482 constitutes the refereed conference proceedings of the 27th International Conference on Industrial, Engineering and Other Applications of Applied Intelligent Systems, IEA/AIE 2014, held in Kaohsiung, Taiwan, in June 2014. The total of 106 papers selected for the proceedings were carefully reviewed and selected from various submissions. The papers deal with a wide range of topics from applications of applied intelligent systems to solve real-life problems in all areas including engineering, science, industry, automation and robotics, business and finance, medicine and biomedicine, bioinformatics, cyberspace and human-machine interaction.
Download or read book Prognostics written by Kai Goebel and published by Createspace Independent Publishing Platform. This book was released on 2017-04-03 with total page 396 pages. Available in PDF, EPUB and Kindle. Book excerpt: Prognostics is the science of making predictions of engineering systems. It is part of a suite of techniques that determine whether a system is behaving within nominal operational performance and - if it does not - that determine what is wrong and how long it will take until the system no longer fulfills certain functional requirements. This book presents the latest developments and research findings on the topic of prognostics by the Prognostics Center of Excellence at NASA Ames Research Center. The book is intended to provide a practitioner with an understanding of the foundational concepts as well as practical tools to perform prognostics and health management on different types of engineering systems and in particular to predict remaining useful life.
Download or read book Diagnostic Techniques in Industrial Engineering written by Mangey Ram and published by Springer. This book was released on 2017-10-20 with total page 254 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book presents the most important tools, techniques, strategy and diagnostic methods used in industrial engineering. The current widely accepted methods of diagnosis and their properties are discussed. Also, the possible fruitful areas for further research in the field are identified.
Download or read book Machine Learning and Artificial Intelligence for Agricultural Economics written by Chandrasekar Vuppalapati and published by Springer Nature. This book was released on 2021-10-04 with total page 611 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book discusses machine learning and artificial intelligence (AI) for agricultural economics. It is written with a view towards bringing the benefits of advanced analytics and prognostics capabilities to small scale farmers worldwide. This volume provides data science and software engineering teams with the skills and tools to fully utilize economic models to develop the software capabilities necessary for creating lifesaving applications. The book introduces essential agricultural economic concepts from the perspective of full-scale software development with the emphasis on creating niche blue ocean products. Chapters detail several agricultural economic and AI reference architectures with a focus on data integration, algorithm development, regression, prognostics model development and mathematical optimization. Upgrading traditional AI software development paradigms to function in dynamic agricultural and economic markets, this volume will be of great use to researchers and students in agricultural economics, data science, engineering, and machine learning as well as engineers and industry professionals in the public and private sectors.
Download or read book Applications of Artificial Intelligence in Process Systems Engineering written by Jingzheng Ren and published by Elsevier. This book was released on 2021-06-05 with total page 542 pages. Available in PDF, EPUB and Kindle. Book excerpt: Applications of Artificial Intelligence in Process Systems Engineering offers a broad perspective on the issues related to artificial intelligence technologies and their applications in chemical and process engineering. The book comprehensively introduces the methodology and applications of AI technologies in process systems engineering, making it an indispensable reference for researchers and students. As chemical processes and systems are usually non-linear and complex, thus making it challenging to apply AI methods and technologies, this book is an ideal resource on emerging areas such as cloud computing, big data, the industrial Internet of Things and deep learning. With process systems engineering's potential to become one of the driving forces for the development of AI technologies, this book covers all the right bases. Explains the concept of machine learning, deep learning and state-of-the-art intelligent algorithms Discusses AI-based applications in process modeling and simulation, process integration and optimization, process control, and fault detection and diagnosis Gives direction to future development trends of AI technologies in chemical and process engineering
