Download or read book Machine Learning Support for Fault Diagnosis of System on Chip written by Patrick Girard and published by Springer Nature. This book was released on 2023-03-13 with total page 320 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book provides a state-of-the-art guide to Machine Learning (ML)-based techniques that have been shown to be highly efficient for diagnosis of failures in electronic circuits and systems. The methods discussed can be used for volume diagnosis after manufacturing or for diagnosis of customer returns. Readers will be enabled to deal with huge amount of insightful test data that cannot be exploited otherwise in an efficient, timely manner. After some background on fault diagnosis and machine learning, the authors explain and apply optimized techniques from the ML domain to solve the fault diagnosis problem in the realm of electronic system design and manufacturing. These techniques can be used for failure isolation in logic or analog circuits, board-level fault diagnosis, or even wafer-level failure cluster identification. Evaluation metrics as well as industrial case studies are used to emphasize the usefulness and benefits of using ML-based diagnosis techniques.
Download or read book Machine Learning Based Fault Diagnosis for Industrial Engineering Systems written by Rui Yang and published by CRC Press. This book was released on 2022-06-16 with total page 93 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book provides advanced techniques for precision compensation and fault diagnosis of precision motion systems and rotating machinery. Techniques and applications through experiments and case studies for intelligent precision compensation and fault diagnosis are offered along with the introduction of machine learning and deep learning methods. Machine Learning-Based Fault Diagnosis for Industrial Engineering Systems discusses how to formulate and solve precision compensation and fault diagnosis problems. The book includes experimental results on hardware equipment used as practical examples throughout the book. Machine learning and deep learning methods used in intelligent precision compensation and intelligent fault diagnosis are introduced. Applications to deal with relevant problems concerning CNC machining and rotating machinery in industrial engineering systems are provided in detail along with applications used in precision motion systems. Methods, applications, and concepts offered in this book can help all professional engineers and students across many areas of engineering and operations management that are involved in any part of Industry 4.0 transformation.
Download or read book Deep Neural Networks Enabled Intelligent Fault Diagnosis of Mechanical Systems written by Ruqiang Yan and published by CRC Press. This book was released on 2024-06-06 with total page 217 pages. Available in PDF, EPUB and Kindle. Book excerpt: The book aims to highlight the potential of deep learning (DL)-enabled methods in intelligent fault diagnosis (IFD), along with their benefits and contributions. The authors first introduce basic applications of DL-enabled IFD, including auto-encoders, deep belief networks, and convolutional neural networks. Advanced topics of DL-enabled IFD are also explored, such as data augmentation, multi-sensor fusion, unsupervised deep transfer learning, neural architecture search, self-supervised learning, and reinforcement learning. Aiming to revolutionize the nature of IFD, Deep Neural Networks-Enabled Intelligent Fault Diangosis of Mechanical Systems contributes to improved efficiency, safety, and reliability of mechanical systems in various industrial domains. The book will appeal to academic researchers, practitioners, and students in the fields of intelligent fault diagnosis, prognostics and health management, and deep learning.
Download or read book Knowledge Driven Board Level Functional Fault Diagnosis written by Fangming Ye and published by Springer. This book was released on 2016-08-19 with total page 154 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book provides a comprehensive set of characterization, prediction, optimization, evaluation, and evolution techniques for a diagnosis system for fault isolation in large electronic systems. Readers with a background in electronics design or system engineering can use this book as a reference to derive insightful knowledge from data analysis and use this knowledge as guidance for designing reasoning-based diagnosis systems. Moreover, readers with a background in statistics or data analytics can use this book as a practical case study for adapting data mining and machine learning techniques to electronic system design and diagnosis. This book identifies the key challenges in reasoning-based, board-level diagnosis system design and presents the solutions and corresponding results that have emerged from leading-edge research in this domain. It covers topics ranging from highly accurate fault isolation, adaptive fault isolation, diagnosis-system robustness assessment, to system performance analysis and evaluation, knowledge discovery and knowledge transfer. With its emphasis on the above topics, the book provides an in-depth and broad view of reasoning-based fault diagnosis system design. • Explains and applies optimized techniques from the machine-learning domain to solve the fault diagnosis problem in the realm of electronic system design and manufacturing;• Demonstrates techniques based on industrial data and feedback from an actual manufacturing line;• Discusses practical problems, including diagnosis accuracy, diagnosis time cost, evaluation of diagnosis system, handling of missing syndromes in diagnosis, and need for fast diagnosis-system development.
Download or read book Intelligent Fault Diagnosis and Health Assessment for Complex Electro Mechanical Systems written by Weihua Li and published by Springer Nature. This book was released on 2023-09-10 with total page 474 pages. Available in PDF, EPUB and Kindle. Book excerpt: Based on AI and machine learning, this book systematically presents the theories and methods for complex electro-mechanical system fault prognosis, intelligent diagnosis, and health state assessment in modern industry. The book emphasizes feature extraction, incipient fault prediction, fault classification, and degradation assessment, which are based on supervised-, semi-supervised-, manifold-, and deep learning; machinery degradation state tracking and prognosis by phase space reconstruction; and complex electro-mechanical system reliability assessment and health maintenance based on running state info. These theories and methods are integrated with practical industrial applications, which can help the readers get into the field more smoothly and provide an important reference for their study, research, and engineering practice.
Download or read book Computational Intelligence for Cybersecurity Management and Applications written by Yassine Maleh and published by CRC Press. This book was released on 2023-04-28 with total page 249 pages. Available in PDF, EPUB and Kindle. Book excerpt: As cyberattacks continue to grow in complexity and number, computational intelligence is helping under-resourced security analysts stay one step ahead of threats. Drawing on threat intelligence from millions of studies, blogs, and news articles, computational intelligence techniques such as machine learning and automatic natural language processing quickly provide the means to identify real threats and dramatically reduce response times. The book collects and reports on recent high-quality research addressing different cybersecurity challenges. It: explores the newest developments in the use of computational intelligence and AI for cybersecurity applications provides several case studies related to computational intelligence techniques for cybersecurity in a wide range of applications (smart health care, blockchain, cyber-physical system, etc.) integrates theoretical and practical aspects of computational intelligence for cybersecurity so that any reader, from novice to expert, may understand the book’s explanations of key topics. It offers comprehensive coverage of the essential topics, including: machine learning and deep learning for cybersecurity blockchain for cybersecurity and privacy security engineering for cyber-physical systems AI and data analytics techniques for cybersecurity in smart systems trust in digital systems This book discusses the current state-of-the-art and practical solutions for the following cybersecurity and privacy issues using artificial intelligence techniques and cutting-edge technology. Readers interested in learning more about computational intelligence techniques for cybersecurity applications and management will find this book invaluable. They will get insight into potential avenues for future study on these topics and be able to prioritize their efforts better.
Download or read book Unsupervised Process Monitoring and Fault Diagnosis with Machine Learning Methods written by Chris Aldrich and published by Springer Science & Business Media. This book was released on 2013-06-15 with total page 388 pages. Available in PDF, EPUB and Kindle. Book excerpt: This unique text/reference describes in detail the latest advances in unsupervised process monitoring and fault diagnosis with machine learning methods. Abundant case studies throughout the text demonstrate the efficacy of each method in real-world settings. The broad coverage examines such cutting-edge topics as the use of information theory to enhance unsupervised learning in tree-based methods, the extension of kernel methods to multiple kernel learning for feature extraction from data, and the incremental training of multilayer perceptrons to construct deep architectures for enhanced data projections. Topics and features: discusses machine learning frameworks based on artificial neural networks, statistical learning theory and kernel-based methods, and tree-based methods; examines the application of machine learning to steady state and dynamic operations, with a focus on unsupervised learning; describes the use of spectral methods in process fault diagnosis.
Download or read book Filter Based Fault Diagnosis and Remaining Useful Life Prediction written by Yong Zhang and published by CRC Press. This book was released on 2023-02-10 with total page 290 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book unifies existing and emerging concepts concerning state estimation, fault detection, fault isolation and fault estimation on industrial systems with an emphasis on a variety of network-induced phenomena, fault diagnosis and remaining useful life for industrial equipment. It covers state estimation/monitor, fault diagnosis and remaining useful life prediction by drawing on the conventional theories of systems science, signal processing and machine learning. Features: Unifies existing and emerging concepts concerning robust filtering and fault diagnosis with an emphasis on a variety of network-induced complexities. Explains theories, techniques, and applications of state estimation as well as fault diagnosis from an engineering-oriented perspective. Provides a series of latest results in robust/stochastic filtering, multidate sample, and time-varying system. Captures diagnosis (fault detection, fault isolation and fault estimation) for time-varying multi-rate systems. Includes simulation examples in each chapter to reflect the engineering practice. This book aims at graduate students, professionals and researchers in control science and application, system analysis, artificial intelligence, and fault diagnosis.
Download or read book Machine Learning for Cyber Physical Systems written by Jürgen Beyerer and published by Springer. This book was released on 2019-04-09 with total page 87 pages. Available in PDF, EPUB and Kindle. Book excerpt: The work presents new approaches to Machine Learning for Cyber Physical Systems, experiences and visions. It contains some selected papers from the international Conference ML4CPS – Machine Learning for Cyber Physical Systems, which was held in Lemgo, October 25th-26th, 2017. Cyber Physical Systems are characterized by their ability to adapt and to learn: They analyze their environment and, based on observations, they learn patterns, correlations and predictive models. Typical applications are condition monitoring, predictive maintenance, image processing and diagnosis. Machine Learning is the key technology for these developments.
Download or read book Big Data Driven Intelligent Fault Diagnosis and Prognosis for Mechanical Systems written by Yaguo Lei and published by Springer Nature. This book was released on 2022-10-19 with total page 292 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book presents systematic overviews and bright insights into big data-driven intelligent fault diagnosis and prognosis for mechanical systems. The recent research results on deep transfer learning-based fault diagnosis, data-model fusion remaining useful life (RUL) prediction, etc., are focused on in the book. The contents are valuable and interesting to attract academic researchers, practitioners, and students in the field of prognostics and health management (PHM). Essential guidelines are provided for readers to understand, explore, and implement the presented methodologies, which promote further development of PHM in the big data era. Features: Addresses the critical challenges in the field of PHM at present Presents both fundamental and cutting-edge research theories on intelligent fault diagnosis and prognosis Provides abundant experimental validations and engineering cases of the presented methodologies
Download or read book Fault Diagnosis written by Józef Korbicz and published by Springer Science & Business Media. This book was released on 2012-12-06 with total page 936 pages. Available in PDF, EPUB and Kindle. Book excerpt: This comprehensive work presents the status and likely development of fault diagnosis, an emerging discipline of modern control engineering. It covers fundamentals of model-based fault diagnosis in a wide context, providing a good introduction to the theoretical foundation and many basic approaches of fault detection.
Download or read book Artificial Intelligence in Process Fault Diagnosis written by Richard J. Fickelscherer and published by John Wiley & Sons. This book was released on 2024-02-21 with total page 436 pages. Available in PDF, EPUB and Kindle. Book excerpt: Artificial Intelligence in Process Fault Diagnosis A comprehensive guide to the future of process fault diagnosis Automation has revolutionized every aspect of industrial production, from the accumulation of raw materials to quality control inspections. Even process analysis itself has become subject to automated efficiencies, in the form of process fault analyzers, i.e., computer programs capable of analyzing process plant operations to identify faults, improve safety, and enhance productivity. Prohibitive cost and challenges of application have prevented widespread industry adoption of this technology, but recent advances in artificial intelligence promise to place these programs at the center of manufacturing process analysis. Artificial Intelligence in Process Fault Diagnosis brings together insights from data science and machine learning to deliver an effective introduction to these advances and their potential applications. Balancing theory and practice, it walks readers through the process of choosing an ideal diagnostic methodology and the creation of intelligent computer programs. The result promises to place readers at the forefront of this revolution in manufacturing. Artificial Intelligence in Process Fault Diagnosis readers will also find: Coverage of various AI-based diagnostic methodologies elaborated by leading experts Guidance for creating programs that can prevent catastrophic operating disasters, reduce downtime after emergency process shutdowns, and more Comprehensive overview of optimized best practices Artificial Intelligence in Process Fault Diagnosis is ideal for process control engineers, operating engineers working with processing industrial plants, and plant managers and operators throughout the various process industries.
Download or read book Machine Learning Paradigms written by George A. Tsihrintzis and published by Springer. This book was released on 2019-07-06 with total page 548 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book is the inaugural volume in the new Springer series on Learning and Analytics in Intelligent Systems. The series aims at providing, in hard-copy and soft-copy form, books on all aspects of learning, analytics, advanced intelligent systems and related technologies. These disciplines are strongly related and mutually complementary; accordingly, the new series encourages an integrated approach to themes and topics in these disciplines, which will result in significant cross-fertilization, research advances and new knowledge creation. To maximize the dissemination of research findings, the series will publish edited books, monographs, handbooks, textbooks and conference proceedings. This book is intended for professors, researchers, scientists, engineers and students. An extensive list of references at the end of each chapter allows readers to probe further into those application areas that interest them most.
Download or read book Smart Micro and Nanomaterials for Pharmaceutical Applications written by Ajit Behera and published by CRC Press. This book was released on 2024-08-27 with total page 348 pages. Available in PDF, EPUB and Kindle. Book excerpt: Smart drug delivery refers to a targeted drug delivery or precision drug delivery system that allows drugs to be administered to a specific location in the body or at a specific time with enhanced precision and control. This approach has several advantages, including maximizing the therapeutic effects of a drug while minimizing side effects. This book presents various stimuli-responsive micro- and nanomaterials for pharmaceutical industries. This volume: Covers the global market perspective of micro- and nano-smart materials in pharmaceutical industries. Details various processing routes. Discusses mechanisms for target release. Addresses applications in oral drug delivery, anticancer agents, anti-tumor drug delivery, and drugs for management of infection. This reference work is written to support researchers in the fields of materials engineering and biotechnology with the goal of improving the diagnosis and treatment of disease and patient quality of life.
Download or read book Water Quality Monitoring and Management written by Daoliang Li and published by Academic Press. This book was released on 2018-10-11 with total page 382 pages. Available in PDF, EPUB and Kindle. Book excerpt: Water Quality Monitoring and Management: Basis, Technology and Case Studies presents recent innovations in operations management for water quality monitoring. It highlights the cost of using and choosing smart sensors with advanced engineering approaches that have been applied in water quality monitoring management, including area coverage planning and sequential scheduling. In parallel, the book covers newly introduced technologies like bulk data handling techniques, IoT of agriculture, and compliance with environmental considerations. Presented from a system engineering perspective, the book includes aspects on advanced optimization, system and platform, Wireless Sensor Network, selection of river water quality, groundwater quality detection, and more. It will be an ideal resource for students, researchers and those working daily in agriculture who must maintain acceptable water quality. Discusses field operations research and application in water science Includes detection methods and case analysis for water quality management Encompasses rivers, lakes, seas and groundwater Covers water for agriculture, aquaculture, drinking and industrial uses
Download or read book Enhancing Software Fault Prediction With Machine Learning Emerging Research and Opportunities written by Rashid, Ekbal and published by IGI Global. This book was released on 2017-09-13 with total page 143 pages. Available in PDF, EPUB and Kindle. Book excerpt: Software development and design is an intricate and complex process that requires a multitude of steps to ultimately create a quality product. One crucial aspect of this process is minimizing potential errors through software fault prediction. Enhancing Software Fault Prediction With Machine Learning: Emerging Research and Opportunities is an innovative source of material on the latest advances and strategies for software quality prediction. Including a range of pivotal topics such as case-based reasoning, rate of improvement, and expert systems, this book is an ideal reference source for engineers, researchers, academics, students, professionals, and practitioners interested in novel developments in software design and analysis.
Download or read book Fault Diagnosis in Aircraft Fuel System Components with Machine Learning Algorithms written by Nithya Subramanian and published by . This book was released on 2022 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt:
