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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.
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.
Intelligent Fault Diagnosis and Remaining Useful Life Prediction of Rotating Machinery provides a comprehensive introduction of intelligent fault diagnosis and RUL prediction based on the current achievements of the author's research group. The main contents include multi-domain signal processing and feature extraction, intelligent diagnosis models, clustering algorithms, hybrid intelligent diagnosis strategies, and RUL prediction approaches, etc. This book presents fundamental theories and advanced methods of identifying the occurrence, locations, and degrees of faults, and also includes information on how to predict the RUL of rotating machinery. Besides experimental demonstrations, many application cases are presented and illustrated to test the methods mentioned in the book. This valuable reference provides an essential guide on machinery fault diagnosis that helps readers understand basic concepts and fundamental theories. Academic researchers with mechanical engineering or computer science backgrounds, and engineers or practitioners who are in charge of machine safety, operation, and maintenance will find this book very useful. - Provides a detailed background and roadmap of intelligent diagnosis and RUL prediction of rotating machinery, involving fault mechanisms, vibration characteristics, health indicators, and diagnosis and prognostics - Presents basic theories, advanced methods, and the latest contributions in the field of intelligent fault diagnosis and RUL prediction - Includes numerous application cases, and the methods, algorithms, and models introduced in the book are demonstrated by industrial experiences
This book is a comprehensive, structural approach to fault diagnosis strategy. The different fault types, signal processing techniques, and loss characterisation are addressed in the book. This is essential reading for work with induction motors for transportation and energy.
Decisions of international courts and arbitrators, as well as judgments of national courts, are fundamental elements of modern public international law. The International Law Reports is the only publication in the world wholly devoted to the regular and systematic reporting in English of such decisions. It is therefore an absolutely essential work of reference. Volume 187 is devoted to the Certain Activities Carried Out by Nicaragua in the Border Area (Costa Rica v. Nicaragua) and the Construction of a Road in Costa Rica along the San Juan River (Nicaragua v. Costa Rica), and Opinion 1/17 (EU-Canada Comprehensive Economic and Trade Agreement [CETA Opinion]).
Artificial intelligence (AI) is taking an increasingly important role in our society. From cars, smartphones, airplanes, consumer applications, and even medical equipment, the impact of AI is changing the world around us. The ability of machines to demonstrate advanced cognitive skills in taking decisions, learn and perceive the environment, predict certain behavior, and process written or spoken languages, among other skills, makes this discipline of paramount importance in today's world. Although AI is changing the world for the better in many applications, it also comes with its challenges. This book encompasses many applications as well as new techniques, challenges, and opportunities in this fascinating area.
Power System Fault Diagnosis: A Wide Area Measurement Based Intelligent Approach is a comprehensive overview of the growing interests in efficient diagnosis of power system faults to reduce outage duration and revenue losses by expediting the restoration process.This book illustrates intelligent fault diagnosis schemes for power system networks, at both transmission and distribution levels, using data acquired from phasor measurement units. It presents the power grid modeling, fault modeling, feature extraction processes, and various fault diagnosis techniques, including artificial intelligence techniques, in steps. The book also incorporates uncertainty associated with line parameters, fault information (resistance and inception angle), load demand, renewable energy generation, and measurement noises. - Provides step-by-step modeling of power system networks (distribution and transmission) and faults in MATLAB/SIMULINK and real-time digital simulator (RTDS) platforms - Presents feature extraction processes using advanced signal processing techniques (discrete wavelet and Stockwell transforms) and an easy-to-understand optimal feature selection method - Illustrates comprehensive results in the graphical and tabular formats that can be easily reproduced by beginners - Highlights various utility practices for fault location in transmission networks, distribution systems, and underground cables.
Kirchhoff’s laws give a mathematical description of electromechanics. Similarly, translational motion mechanics obey Newton’s laws, while rotational motion mechanics comply with Euler’s moment equations, a set of three nonlinear, coupled differential equations. Nonlinearities complicate the mathematical treatment of the seemingly simple action of rotating, and these complications lead to a robust lineage of research culminating here with a text on the ability to make rigid bodies in rotation become self-aware, and even learn. This book is meant for basic scientifically inclined readers commencing with a first chapter on the basics of stochastic artificial intelligence to bridge readers to very advanced topics of deterministic artificial intelligence, espoused in the book with applications to both electromechanics (e.g. the forced van der Pol equation) and also motion mechanics (i.e. Euler’s moment equations). The reader will learn how to bestow self-awareness and express optimal learning methods for the self-aware object (e.g. robot) that require no tuning and no interaction with humans for autonomous operation. The topics learned from reading this text will prepare students and faculty to investigate interesting problems of mechanics. It is the fondest hope of the editor and authors that readers enjoy the book.
A knowledge-based system (KBS) is a system that uses artificial intelligence techniques in problem-solving processes to support human decision-making, learning, and action. Ideal for advanced-undergraduate and graduate students, as well as business professionals, this text is designed to help users develop an appreciation of KBS and their architecture and understand a broad variety of knowledge-based techniques for decision support and planning. It assumes basic computer science skills and a math background that includes set theory, relations, elementary probability, and introductory concepts of artificial intelligence. Each of the 12 chapters is designed to be modular, providing instructors with the flexibility to model the book to their own course needs. Exercises are incorporated throughout the text to highlight certain aspects of the material presented and to simulate thought and discussion. A comprehensive text and resource, Knowledge-Based Systems provides access to the most current information in KBS and new artificial intelligences, as well as neural networks, fuzzy logic, genetic algorithms, and soft systems.
This book presents refereed proceedings of the Second International Conference Neural Computing for Advanced Applications, NCAA 2021, held in Guangzhou, China, in August, 2021. The 54 full papers papers were thorougly reviewed and selected from a total of 144 qualified submissions. The papers are organized in topical sections on neural network theory, cognitive sciences, neuro-system hardware implementations, and NN-based engineering applications; machine learning, data mining, data security and privacy protection, and data-driven applications; neural computing-based fault diagnosis, fault forecasting, prognostic management, and system modeling; computational intelligence, nature-inspired optimizers, and their engineering applications; fuzzy logic, neuro-fuzzy systems, decision making, and their applications in management sciences; control systems, network synchronization, system integration, and industrial artificial intelligence; computer vision, image processing, and their industrial applications; cloud/edge/fog computing, the Internet of Things/Vehicles(IoT/IoV), and their system optimization; spreading dynamics, forecasting, and other intelligent techniques against coronavirus disease (COVID-19).