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Predictive Maintenance of Aircraft Engine using Deep Learning Technique
- Hermawan, Ade Pitra;
- Kim, Dong-Seong;
- Lee, Jae-Min
초록
In this paper, an accurate algorithm to estimate remaining useful life of aircraft engine is proposed. Since the aircraft engine has a low fault tolerant, meaning that a little faulty in the system can lead to catastrophic conditions, an accurate and real-time information about the engine condition is required. This paper utilizes the combination of CNN and LSTM algorithms in learning the behavior of the historical data and providing the accurate information about the time to failure of the system. The simulation results demonstrate that the proposed system is able to achieve improved performance in terms of accuracy rate and computing time compared to the previous works.
- 제목
- Predictive Maintenance of Aircraft Engine using Deep Learning Technique
- 저자
- Hermawan, Ade Pitra; Kim, Dong-Seong; Lee, Jae-Min
- 발행일
- 2020-10
- 학회명
- 11th International Conference on Information and Communication Technology Convergence (ICTC) - Data, Network, and AI in the age of Untact (ICTC)
- 개최지
- Jeju, SOUTH KOREA
- 개최국가
- 미국
- 학회 개최일
- 2020-10-21 ~ 2020-10-23
- 언어
- ENG