RESEARCH PAPERS
Zhao, F., Lai, M.C. and Harrington, D.L, “Automotive Spark-Ignited Direct -Injection Gasoline Engines,” Progress in Energy and Combustion Science, Vol. 25, No. 5, pp. 437-562, 1999.
10.1016/S0360-1285(99)00004-0Duronio, F., De Vita, A., Allocca, L. and Anatone, M., “Gasoline direct injection engines–A review of latest technologies and trends, Part 1: Spray breakup process,” Fuel, Vol. 265, pp. 116948, 2020.
10.1016/j.fuel.2019.116948Duronio, F., De Vita, A., Montanaro, A. and Villante, C., “Gasoline direct injection engines–A review of latest technologies and trends, Part 2,” Fuel, Vol. 265, pp. 116947, 2020.
10.1016/j.fuel.2019.116947Spicher, U, Reissing, J., Kech, J.M. and Gindele, J., “Gasoline Direct Injection (GDI) engines-Development Potentialities,” Technical Report, SAE Technical Paper 1999-01-2938, 1999.
10.4271/1999-01-2938Cavina, N., Businaro, A., Rojo, N., De Cesare, M., Paiano, L. and Cerofolini, A., “Combustion and intake/exhaust systems diagnosis based on acoustic emissions of a GDI TC engine,” Energy Procedia, Vol. 101, pp. 677–684, 2016.
10.1016/j.egypro.2016.11.086Chen, H., Liu, H., Chu, X., Liu, Q. and Xue, D., “Anomaly detection and critical SCADA parameters identification for wind turbines based on LSTM-AE neural network,” Renewable Energy, Vol. 172, pp. 829-840, 2021.
10.1016/j.renene.2021.03.078Li, Z., Li, J., Wang, Y. and Wang, K., “A deep learning approach for anomaly detection based on SAE and LSTM in mechanical equipment,” The International Journal of Advanced Manufacturing Technology, Vol. 103, pp. 499-510, 2019.
10.1007/s00170-019-03557-wQu, C., Zhou, Z., Liu, Z. and Jia, S., “Predictive anomaly detection for marine diesel engine based on echo state network and autoencoder,” Energy Reports, Vol. 8, pp. 998-1003, 2022.
10.1016/j.egyr.2022.01.225Wielgosz, M., Skoczeń, A. and De Matteis, E., “Protection of superconducting industrial machinery using RNN-based anomaly detection for implementation in smart sensor,” Sensors, Vol. 18, No. 11, p. 3933, 2018.
10.3390/s1811393330441813PMC6264111Lee, M., “Early warning detection of thermoacoustic instability using three-dimensional complexity-entropy causality space,” Experimental Thermal and Fluid Science, Vol. 130, p. 110517, 2022.
10.1016/j.expthermflusci.2021.110517Han, E., Kim, D., Lee, J., Kim, Y., Yi, M. and Lee, M., “Analysis of the Hall-Effect Thruster Discharge Blowoff Using Complexity-Entropy Causality Plane,” Journal of the Korean Society for Aeronautical & Space Sciences, Vol. 51, No. 4, pp. 263-271, 2023.
10.5139/JKSAS.2023.51.4.263Son, H. and Lee, M., “A PINN approach for identifying governing parameters of noisy thermoacoustic systems,” Journal of Fluid Mechanics, Vol. 984, p. A21, 2024.
10.1017/jfm.2024.219Vaswani, A., Shazeer, N., Parmar, N., Uszkoreit, J., Jones, L., Gomez, A.N., Kaiser, Ł. and Polosukhin, I., “Attention is all you need,” Advances in Neural Information Processing Systems, Vol. 30, 2017.
Zerveas, G., Jayaraman, S., Patel, D., Bhamidipaty, A. and Eickhoff, C., “A transformer-based framework for multivariate time series representation learning,” 27th ACM SIGKDD Conference on Knowledge Discovery & Data Mining, Singapore, pp. 2114-2124, Aug. 2021.
10.1145/3447548.3467401Jin, Y., Hou, L. and Chen, Y., “A time series transformer based method for the rotating machinery fault diagnosis,” Neurocomputing, Vol. 494, pp. 379-395, 2022.
10.1016/j.neucom.2022.04.111Li, Z., Zhang, X. and Dong, Z., “TSF-transformer: a time series forecasting model for exhaust gas emission using transformer,” Applied Intelligence, Vol. 53, No. 13, pp. 17211-17225, 2023.
10.1007/s10489-022-04326-136590990PMC9788662Lee, M., Kim, K.T., Gupta, V. and Li, L.K.B., “System identification and early warning detection of thermoacoustic oscillations in a turbulent combustor using its noise-induced dynamics,” Proceedings of the Combustion Institute, Vol. 38, No. 4, pp. 6025-6033, 2021.
10.1016/j.proci.2020.06.057- Publisher :The Korean Society of Propulsion Engineers
- Publisher(Ko) :한국추진공학회
- Journal Title :Journal of the Korean Society of Propulsion Engineers
- Journal Title(Ko) :한국추진공학회지
- Volume : 29
- No :4
- Pages :26-32
- Received Date : 2025-03-10
- Revised Date : 2025-04-10
- Accepted Date : 2025-04-22
- DOI :https://doi.org/10.6108/KSPE.2025.29.4.026


Journal of the Korean Society of Propulsion Engineers








