Hybrid Approach for Power Plant Fault Diagnostics [electronic resource] /

By:

Lemma, Tamiru Alemu [author.]

Contributor(s):

SpringerLink (Online service)

Language: ENG Series: Studies in Computational Intelligence ; 743Publisher: Cham : Springer International Publishing : Imprint: Springer, 2018Edition: 1st ed. 2018Description: XII, 283 p. 161 illus., 138 illus. in color. | Binding - Card Paper |Content type:

text

Media type:

computer

Carrier type:

online resource

ISBN:

9783319718712

Subject(s):

Additional physical formats: Printed edition:: No title; Printed edition:: No title; Printed edition:: No titleDDC classification:

006.3 23

Online resources:

Click here to access eBook in Springer Nature platform. (Within Campus only.)

In: Springer Nature eBookSummary: 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.

List(s) this item appears in: Springer Nature eBooks

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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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