Patent Document ID: 9478077
Application ID: 14381207
Patent Status: 1

Claim One:
1. Method of analysing flight data comprising the following steps: obtaining flight data recorded during N flights of at least one aircraft, said flight data have been recorded with a flight data recorder of an aircraft; grouping in a signature vector X i of a flight i, the data corresponding to the flight i said signature vector X i being of size d, the components of the signature vector being the data recorded during said flight i; obtaining a zone of normal flights and classifying the flight signatures X i with respect to their distance to said zone, using a Gaussian kernel entropy component analysis of the flight signatures X i ; determining, for each flight i, an abnormality score z i defined by the distance of a flight signature X i with respect to the zone of normal flights; detecting, as a function of the abnormality score z i , at least one abnormal flight; determining for each abnormal flight, a phantom flight the nearest to the abnormal flight while being in the zone of normal flights, wherein the Gaussian kernel entropy component analysis comprises the following sub-steps: determination of a matrix of similarity K of size N×N, the components of which quantify the proximity between two flight signatures X i ; breakdown into eigen vectors of the matrix of similarity K to obtain N eigen vectors a 1 ,. .. , a N and N eigen values λ 1 ,. .. , λ N such that ∀i=1,. .. , N K·a i =λ i ·a i ; determination for each eigen vector of its entropy coefficient γ i ; selection of a sub-assembly of eigen vectors {a m } mε{1,. .. , N} such that the sum of the entropies γ m is greater than the percentage of the sum of the N entropies γ i .