- Tytuł:
- Residual generator fuzzy identification for automotive diesel engine fault diagnosis
- Autorzy:
- Simani, S.
- Powiązania:
- https://bibliotekanauki.pl/articles/329740.pdf
- Data publikacji:
- 2013
- Wydawca:
- Uniwersytet Zielonogórski. Oficyna Wydawnicza
- Tematy:
-
fault detection
fault isolation
analytical redundancy
Takagi–Sugeno fuzzy prototypes
residual generator fuzzy modelling and identification
real diesel engine
detekcja uszkodzeń
lokalizacja uszkodzeń
redundancja analityczna
silnik Diesla - Opis:
- Safety in dynamic processes is a concern of rising importance, especially if people would be endangered by serious system failure. Moreover, as the control devices which are now exploited to improve the overall performance of processes include both sophisticated control strategies and complex hardware (input-output sensors, actuators, components and processing units), there is an increased probability of faults. As a direct consequence of this, automatic supervision systems should be taken into account to diagnose malfunctions as early as possible. One of the most promising methods for solving this problem relies on the analytical redundancy approach, in which residual signals are generated. If a fault occurs, these residual signals are used to diagnose the malfunction. This paper is focused on fuzzy identification oriented to the design of a bank of fuzzy estimators for fault detection and isolation. The problem is treated in its different aspects covering the model structure, the parameter identification method, the residual generation technique, and the fault diagnosis strategy. The case study of a real diesel engine is considered in order to demonstrate the effectiveness the proposed methodology.
- Źródło:
-
International Journal of Applied Mathematics and Computer Science; 2013, 23, 2; 419-438
1641-876X
2083-8492 - Pojawia się w:
- International Journal of Applied Mathematics and Computer Science
- Dostawca treści:
- Biblioteka Nauki
Artykuł