Machine learning in avionics
    1.
    发明授权

    公开(公告)号:US12033521B2

    公开(公告)日:2024-07-09

    申请号:US16716160

    申请日:2019-12-16

    Applicant: THALES

    CPC classification number: G08G5/0034 G06N3/08 G06N20/00 G08G5/0021

    Abstract: Systems and methods for managing the flight of an aircraft, include the steps of receiving data from recordings of the flight of an aircraft; the data comprising data from sensors and/or data from the onboard avionics; determining the aircraft state at a point N on the basis of the received data; determining the state of the aircraft at the point N+1 on the basis of the state of the aircraft at point N by applying a model learnt by means of machine learning. Developments describe the use of the flight parameters SEP, FF and N1; offline and/or online unsupervised machine learning, according to a variety of algorithms and neural networks. Software aspects are described.

    Decision-making aid for revising a flight plan

    公开(公告)号:US11017677B2

    公开(公告)日:2021-05-25

    申请号:US15700156

    申请日:2017-09-10

    Applicant: THALES

    Abstract: A method is provided for managing the revising of a flight plan of an aircraft implemented by at least two systems, one being of avionics type (qualified, certified) and the other not. From a flight plan, flight plan revisions are determined, even assessed, then one or more of these revisions are selected and/or combined. Subsequently, these combinations are processed by the avionics system and the corresponding avionics parameters are calculated. By comparing the different results of avionics quality, the impact of each revision can be quantified then rendered to the pilot to assist in his or her decision-making, in particular with regard to negotiating the revisions with air traffic control. Combinatorial optimization and learning steps are described, as are system and software aspects.

    Analysis of aircraft trajectories

    公开(公告)号:US12211388B2

    公开(公告)日:2025-01-28

    申请号:US17629737

    申请日:2020-07-23

    Applicant: THALES

    Abstract: Devices and computer-implemented methods for analyzing aircraft trajectories, the method includes the steps of receiving data associated with a plurality of aircraft trajectories; breaking the trajectories down into a plurality of vectors, a vector comprising one or more sequences of enumerators; aligning multiple vectorized trajectories by shifting sequences of enumerators by one or more positions; and detecting one or more anomalies in one or more trajectories by unsupervised classification (e.g. DBSCAN). Developments describe the supervised determination of trajectory anomaly detection models, the use of density-based algorithms, the use of one or more neural networks and/or decision trees, one or more display steps, notably displaying root causes (explainable or understandable artificial intelligence), the processing of avionics data flows, etc. System (e.g. computing) and software aspects are described.

    METHOD FOR VERIFYING THE ABILITY OF AN AIRCRAFT TO ATTAIN AN ENDPOINT, METHOD FOR DETERMINING AN ATTAINABLE AREA, ASSOCIATED COMPUTER PROGRAM PRODUCT AND ANALYSING SYSTEM

    公开(公告)号:US20190390961A1

    公开(公告)日:2019-12-26

    申请号:US16442136

    申请日:2019-06-14

    Applicant: Thales

    Abstract: The present invention relates to a method for verifying the ability of an aircraft to attain an endpoint from a starting point, comprising the steps of supplying an external evolution context of the aircraft, supplying an internal evolution context of the aircraft; calculating a trajectory of the aircraft between the starting point and the endpoint according to the external evolution context and the internal evolution context of the aircraft and according to a predetermined strategy for circumventing three-dimensional obstacles and associating an endpoint attainability state.When there is at least one trajectory between the starting point and the endpoint, the method further comprising a step of estimating a surplus of energy of the aircraft at the endpoint of the calculated trajectory.

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