Monitoring of aircraft operation using statistics and machine learning

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ConferenceProceedings of IEEE International Conference on Tools with Artificial Intelligence, November 9-11, 1999., Chicago, Illinois, USA
AbstractThis paper describes the use of statistics and machine learning techniques to monitor the performance of commercial aircraft operation. The purpose of this research is to develop methods that can be used to generate reliable and timely alerts so that engineers and fleet specialists become aware of abnormal situations in large fleet of commercial aircraft that they manage. We introduce three approaches that we have used for monitoring engines and generating alerts. We also explain how additional information can be generated from machine learning experiments so that the parameters influencing the particular abnormal situation and their ranges are also identified and reported. Various benefits of fleet monitoring are explained in the paper.
Publication date
AffiliationNRC Institute for Information Technology; National Research Council Canada
Peer reviewedNo
NRC number43586
NPARC number9062825
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Record identifier97b10db1-e953-4213-853e-f52e1c41f30e
Record created2009-05-08
Record modified2016-05-09
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