Data based classifiers for identification of aircraft landing characteristics
Abstract »This paper explores the use of machine learning classifiers to distinguish between different aircraft landing characteristics. The context of this problem is the desire to create data-driven models to predict strains on certain components of an aircraft landing gear from measurements recorded at other points on the aircraft. This would include the standard measurements taken by the flight data recorder. There is a high degree of variability in the dynamic experience of landing gear within a landing event and also from one landing to another. Therefore, it is expected that the ability to classify landings according to certain global conditions such as a hard landing or an asymmetric landing, will enable the modelling problem to be divided down into different sub-models that can be applied according to the landing type.
Biography: I completed my PhD in 2013 in the University of Sheffield, Dept of Automatic Control and Systems Engineering Research Associate. I know work as a research associate in the Dynamics Group in the Dept of Mechanical Engineering.
Affiliation: University of Sheffield Mechanical Engineering S1 3JD Sheffield United KingdomThomas, AndrewThomas, Andrew
Affiliation: Messier-Bugatti-Dowty Cheltenham United KingdomCapener, WayneCapener, Wayne firstname.lastname@example.org
Affiliation: Messier-Bugatti-Dowty Gloucester United KingdomWorden, KeithWorden, Keith email@example.com
Affiliation: University of Sheffield Mechanical Engineering Sheffield United Kingdom