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

By: Lemma, Tamiru Alemu., autor.
Material type: materialTypeLabelE-bookSeries: (Studies in Computational Intelligence,, 1860-949X; 743); (Engineering (Springer-11647)).Publisher: Cham : Springer International Publishing, 2018Description: 1 recurso en línea (XII, 283 páginas 161 ilustraciones, 138 ilustraciones a color.).ISBN: 9783319718712.Subject: Ingeniería asistida por ordenador | Visión por ordenador | Inteligencia artificialOnline resources: Acceso a este recurso digital (usuarios Universidad Europea de Madrid)Digital Resources
Contents:
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 Recommendation.
Abstract: 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 alike.
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Holdings
Item type Current library Collection Call number Status Date due Barcode Item holds
LIBRO-E NO PRÉSTAMO LIBRO-E NO PRÉSTAMO Madrid Digital Acceso Electrónico (UEM) Ciencias e Ingeniería Q342 2018 EB (Browse shelf(Opens below)) Acceso electrónico eBook.15112139
Total holds: 0

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 Recommendation.

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 alike.

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