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Estimation de paramètres de vol avion et détection de pannes capteurs

Abstract : The improvement of the aircraft performance and the decrease of the pilots’ workload require more complex new aircraft avionic systems. This complexification paves the way for new constraints, such as improving the availability of the most critical flight parameters used by the pilots (mainly the calibrated airspeed) or by the most advanced flight control systems (as the angle of attack, the altitude pressure or the aircraft weight). Today, their availability is mainly guaranteed by mean of a strong hardware redundancy (triplex type for civil aircraft). However, this solution is perfectible and penalizes the overall system performances in terms of weight, power consumption, space requirements and extra maintenance needs. Some faults, such as common mode failures, which correspond to simultaneous and consistent faults of at least two sensors measuring a same variable, cannot be detected. In this thesis, a solution based on the principle of the so-called analytical redundancy has been developed to detect them and reconstruct through time the missing signals. This solution depends on the measurements, and kinematic and flight dynamic equations available. For instance, the lift force equation combines numerous flight parameters of interest. It is of great value in the data fusion process on condition of having an accurate surrogate model (as lookup tables adjusted with flight data, neural network, etc.) to estimate the lift force coefficient. In the end, an extended Kalman filter has been developed to estimate the critical longitudinal flight parameters. Besides, the existing complementarity between this model-based approach and several signal-based methods has permitted to have sensor faults and weight error diagnosis along with unitary sensor validation capabilities. The architecture and its related embedded algorithms finally developed have been done with respect to the strong industrial constraints (particularly in term of computation burden and formalism). They have been validated using simulation and flight data sets, especially for the isolation of slow drift common mode failures as they represent today the most challenging sensor faults to detect.
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Submitted on : Wednesday, December 19, 2018 - 1:13:29 PM
Last modification on : Wednesday, November 3, 2021 - 3:58:03 AM
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Guillaume Alcalay. Estimation de paramètres de vol avion et détection de pannes capteurs. Performance et fiabilité [cs.PF]. UNIVERSITE DE TOULOUSE, 2018. Français. ⟨tel-01960378⟩



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