Abstract: A data analysis system comprises an artificial intelligence of the machine learning type. The data analysis system collects reference data relating to measurements made and recorded during previous flights of aircraft. A training of the artificial intelligence of the machine learning type is implemented by virtue of reference data, with a first classification run for training to detect potential malfunctions suffered by integrated drive generators and a second classification run for training to determine causes of the malfunctions, where relevant. After using in production, the data analysis system collects data to be analyzed relating to measurements made and recorded during flights of the aircraft comprising an integrated drive generator to be monitored, and uses the artificial intelligence of the machine learning type to predict a potential malfunction and, where relevant, predict its cause using data to be analyzed.

Abstract: In an aircraft, a fuel return valve (FRV) controls a flow of fuel, used to cool an oil feeding a propulsion engine and an oil of an integrated drive generator (IDG). A first sensor supplies measurements of the oil temperature at an output port of the IDG and a second sensor supplies measurements of oil temperature of the propulsion engine. An FRV operation monitoring system: determines, for each flight of the aircraft, an oil temperature maximum at an output port of the IDG and/or a maximum oil temperature of the propulsion engine; assesses a trend of one and/or the other of the oil temperature maxima over several flights; and generates an alarm when the trend of one and/or the other of the oil temperature maxima shows that a predetermined threshold has been exceeded.

Abstract: The disclosure herein proposes identifying precursors to all the phenomena which can have an impact on the service use of an aircraft. It relates to a system for predicting failures in an aircraft, including a processor configured to analyze a current behavior of at least one flight parameter of the aircraft to detect any deviation of the current behavior relative to a predetermined behavior model of the parameter, the behavior model being determined from a plurality of series of learning data relating to the parameter collected during the flights of a set of aircraft.

Abstract: The disclosure herein proposes identifying precursors to all the phenomena which can have an impact on the service use of an aircraft. It relates to a system for predicting failures in an aircraft, including a processor configured to analyze a current behavior of at least one flight parameter of the aircraft to detect any deviation of the current behavior relative to a predetermined behavior model of the parameter, the behavior model being determined from a plurality of series of learning data relating to the parameter collected during the flights of a set of aircraft.

Abstract: The invention concerns a recording and/or storage device comprising at least a camera (V1 to V4) mounted on the vehicle (20) and designed to deliver continuously a series of images and an electronic circuit (21) capable of transferring at every moment, into a buffer (23), the images delivered by the camera (V1 to V4) so that at every moment, said storage contains a sequence of images photographed by the camera for a predetermined time interval preceding said moment, and an impact sensor (25). The transfer of the data contained in the buffer (23), into a storage memory (24) for subsequent playback can be performed in response to a command carried out by the driver or optionally automatically following detection of an impact.