Diagnostics of Mechatronic Systems

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Details

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.


Increases the level of the pedagogical process of universities Presents characteristics of elements reliability, using method, models, and algorithms for diagnostics and by studying examples of model diagnostic systems Written by experts in the field

Inhalt

The basics characteristics of elements reliability.- Methods, models, algorithms for diagnostics of mechatronic systems.- Model systems for diagnosticing of mechatronic objects.- Appendix.

Weitere Informationen

  • Allgemeine Informationen
    • GTIN 09783030670573
    • Lesemotiv Verstehen
    • Genre Mechanical Engineering
    • Auflage 1st edition 2021
    • Sprache Englisch
    • Anzahl Seiten 96
    • Herausgeber Springer International Publishing
    • Größe H235mm x B155mm x T6mm
    • Jahr 2022
    • EAN 9783030670573
    • Format Kartonierter Einband
    • ISBN 3030670570
    • Veröffentlichung 05.03.2022
    • Titel Diagnostics of Mechatronic Systems
    • Autor Pavol Bo Ek , Tibor Krenický , Yury Nikitin
    • Untertitel Studies in Systems, Decision and Control 345
    • Gewicht 160g

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