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Wyświetlanie 1-2 z 2
Tytuł:
Model-based techniques for virtual sensing of longitudinal flight parameters
Autorzy:
Hardier, G.
Seren, C.
Ezerzere, P.
Powiązania:
https://bibliotekanauki.pl/articles/330954.pdf
Data publikacji:
2015
Wydawca:
Uniwersytet Zielonogórski. Oficyna Wydawnicza
Tematy:
model based estimation
fault detection
virtual sensor
Kalman filtering
surrogate modelling
estymacja modelu
detekcja uszkodzeń
sensor wirtualny
filtracja Kalmana
Opis:
Introduction of fly-by-wire and increasing levels of automation significantly improve the safety of civil aircraft, and result in advanced capabilities for detecting, protecting and optimizing A/C guidance and control. However, this higher complexity requires the availability of some key flight parameters to be extended. Hence, the monitoring and consolidation of those signals is a significant issue, usually achieved via many functionally redundant sensors to extend the way those parameters are measured. This solution penalizes the overall system performance in terms of weight, maintenance, and so on. Other alternatives rely on signal processing or model-based techniques that make a global use of all or part of the sensor data available, supplemented by a model-based simulation of the flight mechanics. That processing achieves real-time estimates of the critical parameters and yields dissimilar signals. Filtered and consolidated information is delivered in unfaulty conditions by estimating an extended state vector, including wind components, and can replace failed signals in degraded conditions. Accordingly, this paper describes two model-based approaches allowing the longitudinal flight parameters of a civil A/C to be estimated on-line. Results are displayed to evaluate the performances in different simulated and real flight conditions, including realistic external disturbances and modeling errors.
Źródło:
International Journal of Applied Mathematics and Computer Science; 2015, 25, 1; 23-38
1641-876X
2083-8492
Pojawia się w:
International Journal of Applied Mathematics and Computer Science
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
SMAC-FDI: A single model active fault detection and isolation system for unmanned aircraft
Autorzy:
Ducard, G. J. J.
Powiązania:
https://bibliotekanauki.pl/articles/331366.pdf
Data publikacji:
2015
Wydawca:
Uniwersytet Zielonogórski. Oficyna Wydawnicza
Tematy:
fault detection
fault isolation
unmanned aerial vehicle
Kalman filtering
computationally efficient diagnosis system
active fault diagnosis
artificial excitation system
detekcja uszkodzeń
lokalizacja uszkodzeń
bezzałogowiec
filtracja Kalmana
diagnostyka uszkodzeń
układ wzbudzenia
Opis:
This article presents a single model active fault detection and isolation system (SMAC-FDI) which is designed to efficiently detect and isolate a faulty actuator in a system, such as a small (unmanned) aircraft. This FDI system is based on a single and simple aerodynamic model of an aircraft in order to generate some residuals, as soon as an actuator fault occurs. These residuals are used to trigger an active strategy based on artificial exciting signals that searches within the residuals for the signature of an actuator fault. Fault isolation is carried out through an innovative mechanism that does not use the previous residuals but the actuator control signals directly. In addition, the paper presents a complete parameter-tuning strategy for this FDI system. The novel concepts are backed-up by simulations of a small unmanned aircraft experiencing successive actuator failures. The robustness of the SMAC-FDI method is tested in the presence of model uncertainties, realistic sensor noise and wind gusts. Finally, the paper concludes with a discussion on the computational efficiency of the method and its ability to run on small microcontrollers.
Źródło:
International Journal of Applied Mathematics and Computer Science; 2015, 25, 1; 189-201
1641-876X
2083-8492
Pojawia się w:
International Journal of Applied Mathematics and Computer Science
Dostawca treści:
Biblioteka Nauki
Artykuł
    Wyświetlanie 1-2 z 2

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