A Hybrid Approach for Power Plant Fault Diagnostics / by Tamiru Alemu Lemma

Von:

Lemma, Tamiru Alemu [aut]

Resource type: Ressourcentyp: Buch (Online)Buch (Online)Sprache: Englisch Reihen: Studies in Computational Intelligence ; 743 | SpringerLink Bücher | Springer eBook Collection EngineeringVerlag: Cham : Springer, 2018Beschreibung: Online-Ressource (XII, 283 p. 161 illus., 138 illus. in color, online resource)ISBN:

9783319718712

Schlagwörter:

Andere physische Formen: 9783319718699 | Erscheint auch als: 978-3-319-71869-9 Druck-Ausgabe | Printed edition: 9783319718699 DDC-Klassifikation:

006.3

LOC-Klassifikation:

Q342

DOI: DOI: 10.1007/978-3-319-71871-2Online-Ressourcen:

Zusammenfassung: This book provides a hybrid approach to fault detection and diagnostics. It presents a detailed analysis related to practical applications of the fault detection and diagnostics framework, and highlights recent ﬁndings on power plant nonlinear model identiﬁcation and fault diagnostics. The eﬀectiveness of the methods presented is tested using data acquired from actual cogeneration and cooling plants (CCPs). The models presented were developed by applying Neuro-Fuzzy (NF) methods. The book offers a valuable resource for researchers and practicing engineers alikeZusammenfassung: Introduction -- Literature Review -- Model Identiﬁcation using Neuro-Fuzzy Approach -- Model Uncertainity, Fault Detection and Diagnostics -- Intelligent Fault Detection and Diagnostics -- Application Studies, Part-I: Model Identiﬁcation and Validation -- Application Studies, Part-II: Fault Detection and Diagnostics -- Conclusion and RecommendationPPN: PPN: 1658619870Package identifier: Produktsigel: ZDB-2-ENG | ZDB-2-SEB | ZDB-2-SXE

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