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EN
This paper deals with the fault diagnosis of wind turbines and investigates viable solutions to the problem of earlier fault detection and isolation. The design of the fault indicator, i.e., the fault estimate, involves data-driven approaches, as they can represent effective tools for coping with poor analytical knowledge of the system dynamics, together with noise and disturbances. In particular, the proposed data-driven solutions rely on fuzzy systems and neural networks that are used to describe the strongly nonlinear relationships between measurement and faults. The chosen architectures rely on nonlinear autoregressive models with exogenous input, as they can represent the dynamic evolution of the system along time. The developed fault diagnosis schemes are tested by means of a high-fidelity benchmark model that simulates the normal and the faulty behaviour of a wind turbine. The achieved performances are also compared with those of other model-based strategies from the related literature. Finally, a Monte-Carlo analysis validates the robustness and the reliability of the proposed solutions against typical parameter uncertainties and disturbances.
EN
The article presents key properties of a module intended to estimate non-measurable state variables of an aircraft (afixed-wing aircraft). Sample calculations are applicable to the MP-02A Czajka light Optionally Piloted Vehicle (OPV). The quality of flight parameter values’ estimation is illustrated by comparing flight parameters of the MP-02A Czajka aircraft recorded during actual flight with estimated values of respective parameters calculated during simulation of selected sensor faults. This experiment allows to evaluate the usefulness of the analytical redundancy mechanism that determines attitude parameters (roll, pitch and heading angles) and navigational variables (airspeed, altitude and geographic coordinates).
PL
Artykuł przedstawia główne właściwości modułu estymacji niemierzalnych zmiennych stanu statku powietrznego (stałopłata). Przykładowe obliczenia dotyczą opcjonalnie sterowanego lekkiego samolotu MP-02A Czajka. Jakość oszacowania wartości parametrów lotu obrazuje porównanie zarejestrowanych w rzeczywistym locie parametrów lotu samolotu MP-02A Czajka oraz estymowanych wartości tych parametrów obliczonych dla przypadków symulacji uszkodzenia kolejnych czujników pomiarowych. Eksperyment pozwala ocenić użyteczność mechanizmu redundancji analitycznej dla wyznaczenia parametrów opisujących orientację przestrzenną (kąty przechylenia, pochylenia i kursu) oraz wielkości nawigacyjnych (prędkość i wysokość lotu oraz współrzędne geograficzne).
EN
The problem of detecting and isolating sensor faults (sensor fault detection and isolation—SFDI) on a general aviation aircraft, in the presence of external disturbances, is considered. The proposed approach consists of an extended Kalman observer applied to an augmented aircraft plant, where some integrators are added to the output variables subject to faults. The output of the integrators should be ideally zero in the absence of model uncertainties, external disturbances and sensor faults. A threshold-based decision making system is adopted where the residuals are weighted with gains coming from the solution to an optimization problem. The proposed nonlinear observer was tested both numerically on a large database of simulations in the presence of disturbances and model uncertainties and on input-output data recorded during real flights. In this case, the possibility of successfully applying the proposed technique to detect and isolate faults on inertial and air data sensors, modelled as step or ramp signals artificially added to the real measurements, is shown.
EN
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.
PL
Artykuł prezentuje wybrane przykłady estymacji wielkości krytycznych dla bezpieczeństwa lotu, przy wykorzystaniu wybranych metod analitycznych. Zaprezentowano metodykę wykorzystującą zależności fizyczne pomiędzy zmiennymi estymowanymi i mierzonymi. Pokazano również wykorzystanie obserwatora stanu oraz filtracji Kalmana. Do testowania prezentowanych rozwiązań wykorzystane zostały dane zarejestrowane podczas badań w locie.
EN
The article presents chosen examples of pitch and bank angles estimations. For the estimation, physical equations, state observer and kalman filtering were used. The article discusses properties of estimated values. For testing, flight test data were used.
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