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http://dx.doi.org/10.5139/JKSAS.2018.46.10.823

Automatic Processing Techniques of Rotorcraft Flight Data Using Data Mining  

Oh, Hyeju (Department of Aerospace Engineering, Inha University)
Jo, Sungbeom (Department of Aerospace Engineering, Inha University)
Choi, Keeyoung (Department of Aerospace Engineering, Inha University)
Roh, Eun-Jung (R&D Center, KOREANAIR)
Kang, Byung-Ryong (R&D Center, KOREANAIR)
Publication Information
Journal of the Korean Society for Aeronautical & Space Sciences / v.46, no.10, 2018 , pp. 823-832 More about this Journal
Abstract
In general, the fidelity of the aircraft dynamic model is verified by comparison with the flight test results of the target aircraft. Therefore, the reference flight data for performance comparisons must be extracted. This process requires a lot of time and manpower to extract useful data from the vast quantity of flight test data containing various noise for comparing fidelity. In particular, processing of flight data is complex because rotorcraft have high non-linearity characteristics such as coupling and wake interference effect and perform various maneuvers such as hover and backward flight. This study defines flight data processing criteria for rotorcraft and provides procedures and methods for automated processing of static and dynamic flight data using data mining techniques. Finally, the methods presented are validated using flight data.
Keywords
Rotorcraft; Processing Flight Data; Data Mining; Big Data; Flight Mode Classification;
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