진동분석을 통한 회전익 드론의 블레이드 착빙 예지Prognosis of Blade Icing of Rotorcraft Drones through Vibration Analysis
- Other Titles
- Prognosis of Blade Icing of Rotorcraft Drones through Vibration Analysis
- Authors
- 이선우; 도재석; 허장욱
- Issue Date
- Feb-2024
- Publisher
- 한국군사과학기술학회
- Keywords
- 블레이드 착빙(Blade Icing); 딥러닝(Deep Learning); 드론(Drone); 고장 예지(Fault Prognosis); 건전성 예측및 관리(Prognostics and Health Management)
- Citation
- 한국군사과학기술학회지, v.27, no.1, pp 1 - 7
- Pages
- 7
- Journal Title
- 한국군사과학기술학회지
- Volume
- 27
- Number
- 1
- Start Page
- 1
- End Page
- 7
- URI
- https://scholarworks.bwise.kr/kumoh/handle/2020.sw.kumoh/26593
- ISSN
- 1598-9127
2636-0640
- Abstract
- Weather is one of the main causes of aircraft accidents, and among the phenomena caused by weather, icing is a phenomenon in which an ice layer is formed when an object exposed to an atmosphere below a freezing temperature collides with supercooled water droplets. If this phenomenon occurs in the rotor blades, it causes defects such as severe vibration in the airframe and eventually leads to loss of control and an accident. Therefore, it is necessary to foresee the icing situation so that it can ascend and descend at an altitude without a freezing point. In this study, vibration data in normal and faulty conditions was acquired, data features were extracted, and vibration was predicted through deep learning-based algorithms such as CNN, LSTM, CNN-LSTM, Transformer, and TCN, and performance was compared to evaluate blade icing. A method for minimizing operating loss is suggested.
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Collections - School of Mechanical System Engineering > 1. Journal Articles
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