Lughofer Edwin, Sayed-Mouchaweh Moamar Predictive Maintenance in Dynamic Systems: Advanced Methods, Decision Support Tools and Real-World Applications 9783030056445

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Автор: Lughofer Edwin, Sayed-Mouchaweh Moamar
Название: Predictive Maintenance in Dynamic Systems: Advanced Methods, Decision Support Tools and Real-World Applications
ISBN: 9783030056445
Издательство: Springer
Классификация:

Геология и литосфера

Организация производственных процессов

Техника обеспечения надёжности

Электроника

Техника автоматического регулирования

Техника связи / дальней связи

Компьютерные сети и коммуникации

Искусственный интеллект

ISBN-10: 3030056449
Обложка/Формат: Hardcover
Страницы: 567
Вес: 0.99 кг.
Дата издания: 12.03.2019
Язык: English
Издание: 1st ed. 2019
Иллюстрации: 50 tables, color; 144 illustrations, color; 56 illustrations, black and white; xiii, 567 p. 200 illus., 144 illus. in color.
Размер: 235 x 155 x 32
Читательская аудитория: Professional & vocational
Подзаголовок: Advanced methods, decision support tools and real-world applications
Ссылка на Издательство: Link
Рейтинг:
Поставляется из: Германии
Описание: This book provides a complete picture of several decision support tools for predictive maintenance. These include embedding early anomaly/fault detection, diagnosis and reasoning, remaining useful life prediction (fault prognostics), quality prediction and self-reaction, as well as optimization, control and self-healing techniques. It shows recent applications of these techniques within various types of industrial (production/utilities/equipment/plants/smart devices, etc.) systems addressing several challenges in Industry 4.0 and different tasks dealing with Big Data Streams, Internet of Things, specific infrastructures and tools, high system dynamics and non-stationary environments . Applications discussed include production and manufacturing systems, renewable energy production and management, maritime systems, power plants and turbines, conditioning systems, compressor valves, induction motors, flight simulators, railway infrastructures, mobile robots, cyber security and Internet of Things. The contributors go beyond state of the art by placing a specific focus on dynamic systems, where it is of utmost importance to update system and maintenance models on the fly to maintain their predictive power.
Дополнительное описание: Introduction.- Predictive Maintenance and (Early) FDD in Dynamic Systems.- Beyond State-of-the-Art.- Early Fault Detection and Diagnosis Approaches.- Prognostics and Forecasting.- Self-Reaction and Self-Healing Techniques.- Applications of Predictive Main

Predictive Maintenance in Dynamic Systems: Advanced Methods, Decision Support Tools and Real-World Applications, Lughofer Edwin, Sayed-Mouchaweh Moamar