Acknowledgement
본 연구는 2020년도 산업통산자원부 및 산업기술평가관리원 연구비 지원으로 수행된 '자율운항선박 기술개발사업(20011164, 자율운항선박 핵심 기관시스템 상태 모니터링 및 고장예측 진단기술 개발)'의 연구결과입니다.
References
- Bae, J.H, 2021. Fault detection of aircraft turbofan engine system using a fault detection filter. Institute of Korean Electrical and Electronics Engineers, 25(2), pp.330-336.
- Benkamin, L., Timo, M., Hannes, V., Nasser, J. and Michael, W., 2021. A survey on long short-term memory networks for time series prediction, 14th CIRP 99, pp.650-655.
- Byun, S.I. and Lee, D.I., 2022. Health monitoring for autonomous underwater vehicles using fault tree analysis. Journal of Institute of Control, Robotics and Systems, 28(5), pp. 398-405. https://doi.org/10.5302/J.ICROS.2022.22.0021
- Chae, S.G., Kim, G.R., Bae, B.Y. and Bae, S.J., 2021. Failure diagnosis and prediction for a thermal power plant generator using fastICA. Journal of Applied Reliability, 21(4), pp.341-351. https://doi.org/10.33162/JAR.2021.12.21.4.341
- Cho, H.J., Choi, H.S., Kim, H.J., Nam, K.S., Ryu, J.D. and Ha, K. N., 2022. Feature selection for unmanned surface vehicle fault diagnosis research and experimental verification. Journal of Institute of Control, Robotics and Systems, 28(6), pp.542-550. https://doi.org/10.5302/J.ICROS.2022.22.0046
- Hwang, S.Y., Heo, J.Y., Hong, K.T. and Lee, J.H., 2018. Time series data analysis and fault diagnosis of plant process equipment using statistical machine learning method. Korean Journal of Computational Design and Engineering, 23(3), pp. 193-201. https://doi.org/10.7315/CDE.2018.193
- Kim, S.H, 2022. A study of machine learning technique for noise-based engine fault diagnosis. Journal of the KNST, 5(1), pp.16-19. https://doi.org/10.31818/JKNST.2022.03.5.1.16
- Kim, J.Y., Lee, T.H., Lee, S.H., Lee, J.J., Shin, D.M., Lee, W.K. and Kim, Y.J., 2022. A study on the development of a failure simulation database for condition based maintenance of marine engine system auxiliary equipment. Journal of the Society of Naval Architects of Korea, 59(4), pp.200-206. https://doi.org/10.3744/SNAK.2022.59.4.200
- Kim, S.I., Noh, Y.J., Kang, Y.J., Park, S.H. and Ahn, B.H., 2021. Fault classification model based on time domain feature extraction vibration data. Journal of the Computational Structural Engineering Institute of Korea, 34(I), pp.25-33. https://doi.org/10.7734/COSEIK.2021.34.1.25
- Lee, J.H., 2021. Experimental study on application of an anomaly detection algorithm electric current datasets generated from marine air compressor with time-series features. Journal of the Korean Society of Marine Environment & Safety, 27(1), pp.127-134. https://doi.org/10.7837/kosomes.2021.27.1.127
- Ugo, C., Carlo, C. and Raphael, Z., 2018. Marine gas turbine monitoring and diagnostics by simulation and pattern recognition. International Journal of Naval Architecture and Ocean Engineering, 10, pp.617-628. https://doi.org/10.1016/j.ijnaoe.2017.09.012
- Zhengping, C., Sanjay, P., Cho, K.H., David, S. and Yan, L., 2018. Recurrent neural networks for multivariate time series with missing values, Scientific Reports, 8:6085.