Abstract
The RPAS (Remote Piloted Air System) MILANO is the largest unmanned aerial system developed by INTA that aims to become a research platform capable of carrying out in-flight tests with many scientific payload, thus complementing the Air Research Platforms (PAIs) of INTA. At the structural level, the RPAS MILANO is made in its entirety in carbon / epoxy composite material that is cured out of the autoclave. Its design has been followed by the airworthiness regulations applicable to the aircraft type (STANAG-4671). In the month of December 2018, the RPAS MILANO flight test phase began and it’s Health and Usage Monitoring System (HUMS) is being used to collect data before, after and during flights, providing very useful information when evaluating and analyzing the state of the structure and the possible appearance of structural overloads not foreseen during the mission. Information about special events, such as forced landing or burst loading, can be provided to maintenance operators after each flight. The simulation model and its predictions have been validated in a real structure of the rear fuselage of the MILANO and in which real damage of larger sizes is introduced by eliminating rivets progressively. In our study, three different damage detection algorithms are used, based on a damage index, PCA and Artificial Neural Networks (ANN).
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