A Hybrid Approach for Power Plant Fault Diagnostics
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 effecti...
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| Hlavní autor: | |
|---|---|
| Médium: | Elektronický zdroj E-kniha |
| Jazyk: | angličtina |
| Vydáno: |
Cham :
Springer International Publishing,
2018.
|
| Vydání: | 1st ed. 2018. |
| Edice: | Studies in Computational Intelligence,
743 |
| Témata: | |
| ISBN: | 9783319718712 |
| ISSN: | 1860-949X ; |
| On-line přístup: |
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| 020 | |a 9783319718712 | ||
| 024 | 7 | |a 10.1007/978-3-319-71871-2 |2 doi | |
| 035 | |a CVTIDW10167 | ||
| 040 | |a Springer-Nature |b eng |c CVTISR |e AACR2 | ||
| 041 | |a eng | ||
| 100 | 1 | |a Lemma, Tamiru Alemu. |4 aut | |
| 245 | 1 | 2 | |a A Hybrid Approach for Power Plant Fault Diagnostics |h [electronic resource] / |c by Tamiru Alemu Lemma. |
| 250 | |a 1st ed. 2018. | ||
| 260 | 1 | |a Cham : |b Springer International Publishing, |c 2018. | |
| 300 | |a XII, 283 p. 161 illus., 138 illus. in color. |b online resource. | ||
| 490 | 1 | |a Studies in Computational Intelligence, |x 1860-949X ; |v 743 | |
| 500 | |a Engineering | ||
| 505 | 0 | |a 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. | |
| 516 | |a text file PDF | ||
| 520 | |a 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. | ||
| 650 | 0 | |a Computational intelligence. | |
| 650 | 0 | |a Optical data processing. | |
| 650 | 0 | |a Power electronics. | |
| 650 | 0 | |a Energy systems. | |
| 856 | 4 | 0 | |u http://hanproxy.cvtisr.sk/han/cvti-ebook-springer-eisbn-978-3-319-71871-2 |y Vzdialený prístup pre registrovaných používateľov |
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| 919 | |a 978-3-319-71871-2 | ||
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| 992 | |a SUD | ||
| 999 | |c 275424 |d 275424 | ||