Diagnostics of Mechatronic Systems / by Pavol Božek, Yuri Nikitin, Tibor Krenicky.
By: Božek, Pavol, autor
Contributor(s): Nikitin, Yuri, autor
| Krenicky, Tibor, autor
Material type:
E-bookSeries: (Studies in Systems Decision and Control, 2198-4182; 345); (Intelligent Technologies and Robotics (SpringerNature-42732)); (Intelligent Technologies and Robotics (R0) (SpringerNature-43728)).Publisher: Cham : Springer International Pulishing, 2021Edition: First edition 2021.Description: 1 recurso en línea (XV, 79 páginas) : 43 ilustraciones, 27 ilustraciones a color.ISBN: 9783030670559.Subject: Mecatrónica
| Item type | Current library | Collection | Call number | Status | Date due | Barcode | Item holds | |
|---|---|---|---|---|---|---|---|---|
LIBRO-E NO PRÉSTAMO
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Madrid Digital Acceso Electrónico (UEM) | Ciencias e Ingeniería | TJ213 2021 EB (Browse shelf(Opens below)) | Acceso electrónico | eBook.14032103 |
The basics characteristics of elements reliability -- Methods, models, algorithms for diagnostics of mechatronic systems -- Model systems for diagnosticing of mechatronic objects -- Appendix.
This book provides novel approach to the diagnosis of complex technical systems that are widely used in various kinds of transportation, energy, metallurgy, metalworking, fuels, mining, chemical, paper industries, etc. Effective diagnostic systems are necessary for the early detection of errors in mechatronic systems, for the organization of maintenance and for the assessment of the performed service quality. Unfortunately, the practical use of AI in the diagnosis of mechatronic systems is still quite limited and the inability to build effective mechatronic systems leads to significant economic losses and dangers. The main aim of this book is to contribute to knowledge within the topic of diagnostics of mechatronic systems by the analysis of the elements reliability characteristics, using methods, models and algorithms for diagnostics and by studying examples of model diagnostic systems using AI methods based on neural networks, fuzzy inference systems and genetic algorithms.
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