Aircraft interior monitoring
US-2015321768-A1 · Nov 12, 2015 · US
US9796481B2 · US · B2
| Field | Value |
|---|---|
| Publication number | US-9796481-B2 |
| Application number | US-201514886743-A |
| Country | US |
| Kind code | B2 |
| Filing date | Oct 19, 2015 |
| Priority date | Oct 20, 2014 |
| Publication date | Oct 24, 2017 |
| Grant date | Oct 24, 2017 |
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A method and system for generating an alert report on board an aircraft, comprising an on-board acquiring module configured to acquire data relating to the aircraft, the data originating from sensors and/or equipment installed in the aircraft. An on-board processing module is configured to detect possible anomalies by automatically partitioning the data into a set of homogeneous groups, each anomaly being revealed by a corresponding datum belonging to no homogeneous group. An on-board alert-emitting module is configured to emit an alert report on each detection of an anomaly. An on-board transmitting module is configured to transmit the alert report to the ground and in real-time.
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What is claimed is: 1. A system for generating an alert report on board an aircraft, the system comprising: an on-board acquiring module configured to acquire data relating to the aircraft, the data originating from at least one of sensors and equipment installed in the aircraft; an on-board processing module configured to detect possible anomalies by automatically partitioning the data into a set of homogeneous groups, wherein the processing module is configured to automatically partition the data using a semi-supervised learning technique by comparing the data to abnormal learning data recorded in an on-board knowledge database; an acquiring unit configured to acquire learning data relating to at least one aircraft; a smoothing unit configured to smooth the learning data, thus forming smoothed learning data; a processing unit configured to automatically partition the smoothed learning data using an unsupervised learning technique generating a first class of normal learning data and a second class of abnormal learning data; a recording unit configured to record the abnormal learning data in a knowledge database corresponding to the on-board knowledge database; an on-board alert-emitting module configured to emit an alert report on each detection of an anomaly; and an on-board transmitting module configured to transmit the alert report to the ground and in real-time. 2. The system as claimed in claim 1 , comprising: an on-board buffer memory configured to buffer the data acquired by the acquiring module; and an on-board smoothing module configured to smooth the buffered data before the data is processed by the processing module. 3. The system as claimed in claim 1 , wherein the acquiring unit is configured to acquire the learning data from a first data source comprising ACMS recordings of a set of aircraft and of various flights or other data sources comprising manual requests, electronic logbooks and maintenance reports of the set of aircrafts. 4. An aircraft comprising a generating system as claimed in claim 1 . 5. A method for generating an alert report on board an aircraft, comprising: acquiring data relating to the aircraft originating from at least one of sensors and equipment installed in the aircraft; detecting possible anomalies by automatically partitioning the data into a set of homogeneous groups, wherein the data is partitioned using a semi-supervised learning technique by comparing the data to abnormal learning data recorded in a knowledge database installed on board the aircraft, wherein the knowledge database is constructed on the ground by: acquiring learning data relating to at least one aircraft; smoothing the learning data, thus forming smoothed learning data; automatically partitioning the smoothed learning data using an unsupervised learning technique generating a first class of normal learning data and a second class of abnormal learning data; recording the abnormal learning data in the knowledge database; and installing the knowledge database on board the aircraft; emitting an alert report on each detection of an anomaly; and transmitting the alert report to the ground and in real-time. 6. The method as claimed in claim 5 , comprising periodically updating the knowledge database.
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