Publication

Minjae Kim, Sihyun Yoo, & Ki-Yong Oh, “Real-time monitoring systems of industrial gas turbines with dynamic safety boundary,” (In Preparation)
Sihyun Yoo, Minjae Kim, & Ki-Yong Oh, “An explainable anomaly detection framework for gas turbines with feature selection,” Structural Health Monitoring (IF: 5.7, Submitted)
Minjae Kim, Sihyun Yoo, Seho Son, & Ki-Yong Oh, “Physics-informed deep learning framework for explainable remaining useful life prediction,” Engineering Applications of Artificial Intelligence (IF: 7.5, JCR Top 2%) [pdf]
Minjae Kim, Seho Son, & Ki-Yong Oh, “Margin-maximized hyperspace for fault detection and prediction: A case study with an elevator door,” IEEE Access (IF: 3.9, JCR Top 34%) [pdf]

Minjae Kim, Seho Son, & Ki-Yong Oh, “Sensitivity enhanced method for fault detection and prediction of elevator doors using a margin maximized hyperspace,” Oral presenter at PHM Society 2023, Salt Lake City, Utah, USA.
Minjae Kim, Sihyun Yoo, & Ki-Yong Oh, “Tag selection for the diagnosis of a gas turbine at a combined cycle power plant,” Oral presenter at PHM Korea 2023, Seoul, Korea.
Sihyun Yoo, Minjae Kim, & Ki-Yong Oh, “Anomaly detection of a gas turbine with a variational autoencoder,” PHM Korea 2023, Seoul, Korea.