A Hybrid Approach for Power Plant Fault Diagnostics - Lemma, Tamiru Alemu; SpringerLink (Online service) (Cham : Springer International Publishing : Imprint: Springer, 2018)
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.
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.
Keywords: Computational intelligence; Computer vision; Electric power production; Computational Intelligence; Computer Vision; Electrical Power Engineering; Mechanical Power Engineering