Obiekt
Tytuł: Towards robustness in neural network based fault diagnosis
Współtwórca:
Korbicz, Józef - ed. ; Sauter, Dominique - ed.
Podtytuł:
Tytuł publikacji grupowej:
Abstract:
Challenging design problems arise regularly in modern fault diagnosis systems. Unfortunately, classical analytical techniques often cannot provide acceptable solutions to such difficult tasks. This explains why soft computing techniques such as neural networks become more and more popular in industrial applications of fault diagnosis. ; Taking into account the two crucial aspects, i.e., the nonlinear behaviour of the system being diagnosed as well as the robustness of a fault diagnosis scheme with respect to modelling uncertainty, two different neural network based schemes are described and carefully discussed. The final part of the paper presents an illustrative example regarding the modelling and fault diagnosis of a DC motor, which shows the performance of the proposed strategy.
Wydawca:
Zielona Góra: Uniwersytet Zielonogórski
Identyfikator zasobu:
DOI:
Strony:
Źródło:
AMCS, volume 18, number 4 (2008) ; kliknij tutaj, żeby przejść
Jezyk:
Prawa do dysponowania publikacją:
Biblioteka Uniwersytetu Zielonogórskiego
Kolekcje, do których przypisany jest obiekt:
- Zielonogórska Biblioteka Cyfrowa > Repozytorium > Jednostki organizacyjne > Wydział Informatyki, Elektrotechniki i Automatyki
- Zielonogórska Biblioteka Cyfrowa > Repozytorium > Typy utworów > Artykuły
- Zielonogórska Biblioteka Cyfrowa > Repozytorium > Czasopisma naukowe i serie wydawnicze UZ > International Journal of Applied Mathematics and Computer Science (AMCS)
- Zielonogórska Biblioteka Cyfrowa > Repozytorium > Czasopisma naukowe i serie wydawnicze UZ > International Journal of Applied Mathematics and Computer Science (AMCS) > International Journal of Applied Mathematics and Computer Science (AMCS) (2008)
Data ostatniej modyfikacji:
2024-04-08
Data dodania obiektu:
2024-04-08
Liczba wyświetleń treści obiektu:
3
Wszystkie dostępne wersje tego obiektu:
https://www.zbc.uz.zgora.pl/publication/88504
Wyświetl opis w formacie RDF:
Wyświetl opis w formacie OAI-PMH:
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International Journal of Applied Mathematics and Computer Science (AMCS)
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International Journal of Applied Mathematics and Computer Science (AMCS), volume 25 (2015)
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International Journal of Applied Mathematics and Computer Science (AMCS), volume 24 (2014)
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International Journal of Applied Mathematics and Computer Science (AMCS), volume 23 (2013)
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International Journal of Applied Mathematics and Computer Science (AMCS), volume 22 (2012)
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International Journal of Applied Mathematics and Computer Science (AMCS), volume 21 (2011)
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International Journal of Applied Mathematics and Computer Science (AMCS), volume 20 (2010)
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International Journal of Applied Mathematics and Computer Science (AMCS), volume 19 (2009)
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International Journal of Applied Mathematics and Computer Science (AMCS), volume 18 (2008)
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International Journal of Applied Mathematics and Computer Science (AMCS), volume 18, number 1 (2008)
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International Journal of Applied Mathematics and Computer Science (AMCS), volume 18, number 2 (2008)
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International Journal of Applied Mathematics and Computer Science (AMCS), volume 18, number 3 (2008)
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International Journal of Applied Mathematics and Computer Science (AMCS), volume 18, number 4 (2008)
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- Mechanical analogy of statement networks
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- Configuring a sensor network for fault detection in distributed parameter systems
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- Actuator fault tolerant control design based on a reconfigurable reference input
- Suboptimal fault tolerant control design with the use of discrete optimization
- Decomposition of the symptom observation matrix and grey forecasting in vibration condition monitoring of machines
- Local detection of defects from image sequences
- Fault diagnosis of a water for injection system using enhanced structural isolation
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International Journal of Applied Mathematics and Computer Science (AMCS),volume 1 (1991)
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International Journal of Applied Mathematics and Computer Science (AMCS), volume 25 (2015)
| Nazwa wydania | Data |
|---|---|
| Towards robustness in neural network based fault diagnosis | 2024-04-08 |
