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Wyszukujesz frazę "virtual sensor" wg kryterium: Temat


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:
Artificial Neural Network as a Virtual Sensor of Nitrate Nitrogen (V) Concentration in an Activated Sludge Reactor
Autorzy:
Płonka, Lesław
Powiązania:
https://bibliotekanauki.pl/articles/1838052.pdf
Data publikacji:
2020
Wydawca:
Uniwersytet Zielonogórski. Oficyna Wydawnicza
Tematy:
wastewater treatment
activated sludge process
artificial neural networks
virtual sensor
oczyszczalnia ścieków
reaktor z osadem czynnym
sztuczne sieci neuronowe
czujnik wirtualny
Opis:
The paper discusses the use of an artificial neural network to control the operation of wastewater treatment plants with activated sludge. The task of the neural network in this case is to calculate (predict) the readings of the probe measuring the concentration of nitrate nitrogen (V) in one of the biological reactor tanks. Neural networks are known for their ability to universal approximation of virtually any relationship, including the function of many variables, but the process of "training" the network requires the presentation of many sets of input data and corresponding expected results. This is a difficulty in the case of wastewater treatment plants, because some key process parameters are usually not measured online (samples are taken and measurements are taken in the laboratory), and even if they are, the time intervals are large. Bearing in mind the aforementioned difficulty, this work uses a set of input data consisting only of information that can be measured with measuring probes. As a result of the conducted experiments a high compliance of the probe's prediction with the expected values was obtained. The paper also presents data preparation and the network "training" process.
Źródło:
Civil and Environmental Engineering Reports; 2020, 30, 4; 188-200
2080-5187
2450-8594
Pojawia się w:
Civil and Environmental Engineering Reports
Dostawca treści:
Biblioteka Nauki
Artykuł
    Wyświetlanie 1-2 z 2

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