Airbus Operations (s.a.s.)

Airbus France

Patrice Michel

Philippe Goupil

Rémy Dayre

Hervé Le Berre

Corinne Mailhes

Florian Cazes

Marie Chabert

Cecile Daudet

Embodiments of the disclosure include methods and devices in which a flight parameter vector for an aircraft is automatically estimated and then compared to a threshold to determine whether the flight parameter vector is accurate. The detection device estimates a coefficient vector in an observation window, calculates an estimated flight parameter value, and minimizes an error associated with the observation window when calculating the estimated flight parameter value of the flight parameter vector. Comparisons may be performed by a failure detector or a flight control computer to determine failures impacting the flight parameter vector.

Automatic estimation process and device for a flight parameter vector in an aircraft, as well as detection methods and assemblies for a failure affecting such a vector

The data frequency analysis method comprises: a step for inputting signals coming from a first sensor; a step for inputting signals coming from at least a second sensor, each second sensor being positioned close to the first sensor so that the signals coming from each second sensor are strongly correlated with the signals coming from the first sensor; a step of estimating, for each sensor, a transfer function or model established from the combination of the signals from the first sensor and from each second sensor; and a step of extracting the structural properties of the system from each of the estimated models.

Method and device for frequency analysis of data

Method for analysing the frequency in real-time of a non-stationary signal and corresponding analysis circuit. According to the invention, the signal is sampled, it is digitised, it is broken up into sub-bands. In each sub-band, the signal is modelled by an auto-regressive filter the transfer function of which is of the form 1/A(z). By an adaptive method that is recursive in time and in order, all the polynomials A(z) that have a degree between 1 and a maximum value are calculated. The order of the model is estimated and the polynomial that has this order is retained. The roots of this polynomial are calculated and the components are monitored. The frequency and the amplitude of the sinusoidal components of the signal are thus obtained. Application in aeronautics, electromagnetic, mechanics, seismic prospecting, zoology, etc.

Method and circuit for real time frequency analysis of a non-stationary signal

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Merville, France

Patrice Michel