| A comprehensive review of artificial intelligence-based approaches for rolling element bearing PHM: Shallow and deep learning M Hamadache, JH Jung, J Park, BD Youn JMST Advances 1, 125-151, 2019 | 146 | 2019 |
| Scalable and unsupervised feature engineering using vibration-imaging and deep learning for rotor system diagnosis H Oh, JH Jung, BC Jeon, BD Youn IEEE Transactions on Industrial Electronics 65 (4), 3539-3549, 2017 | 144 | 2017 |
| Vision-based fault diagnostics using explainable deep learning with class activation maps KH Sun, H Huh, BA Tama, SY Lee, JH Jung, S Lee IEEE Access 8, 129169-129179, 2020 | 57 | 2020 |
| Omnidirectional regeneration (ODR) of proximity sensor signals for robust diagnosis of journal bearing systems JH Jung, BC Jeon, BD Youn, M Kim, D Kim, Y Kim Mechanical Systems and Signal Processing 90, 189-207, 2017 | 54 | 2017 |
| A Domain Adaptation with Semantic Clustering (DASC) method for fault diagnosis of rotating machinery M Kim, JU Ko, J Lee, BD Youn, JH Jung, KH Sun ISA transactions 120, 372-382, 2022 | 48 | 2022 |
| Asymmetric inter-intra domain alignments (AIIDA) method for intelligent fault diagnosis of rotating machinery J Lee, M Kim, JU Ko, JH Jung, KH Sun, BD Youn Reliability Engineering & System Safety 218, 108186, 2022 | 47 | 2022 |
| A degenerated equivalent circuit model and hybrid prediction for state-of-health (SOH) of PEM fuel cell T Kim, H Kim, J Ha, K Kim, J Youn, J Jung, BD Youn 2014 international conference on prognostics and health management, 1-7, 2014 | 43 | 2014 |
| Datum unit optimization for robustness of a journal bearing diagnosis system BC Jeon, JH Jung, BD Youn, YW Kim, YC Bae International Journal of Precision Engineering and Manufacturing 16, 2411-2425, 2015 | 33 | 2015 |
| Direct connection-based convolutional neural network (DC-CNN) for fault diagnosis of rotor systems M Kim, JH Jung, JU Ko, HB Kong, J Lee, BD Youn IEEE Access 8, 172043-172056, 2020 | 29 | 2020 |
| Multi-task learning of classification and denoising (MLCD) for noise-robust rotor system diagnosis JU Ko, JH Jung, M Kim, HB Kong, J Lee, BD Youn Computers in Industry 125, 103385, 2021 | 26 | 2021 |
| Statistical approach to diagnostic rules for various malfunctions of journal bearing system using fisher discriminant analysis B Jeon, J Jung, BD Youn, Y Kim, YC Bae PHM Society European Conference 2 (1), 2014 | 17 | 2014 |
| A robust and convex metric for unconstrained optimization in statistical model calibration—probability residual (PR) H Oh, H Choi, JH Jung, BD Youn Structural and Multidisciplinary Optimization 60, 1171-1187, 2019 | 15 | 2019 |
| Smart diagnosis of journal bearing rotor systems: Unsupervised feature extraction scheme by deep learning H Oh, BC Jeon, JH Jung, BD Youn Annual Conference of the PHM Society 8 (1), 2016 | 15 | 2016 |
| A comprehensive review of artificial intelligence-based approaches for rolling element bearing PHM: shallow and deep learning. JMST Advances, 1 (1–2), 125–151 M Hamadache, JH Jung, J Park, BD Youn | 10 | 2019 |
| A hybrid approach of data-driven and physics-based methods for estimation and prediction of fatigue crack growth HB Kong, SH Jo, JH Jung, JM Ha, YC Shin, H Yoon, KH Sun, YH Seo, ... International Journal of Prognostics and Health Management 11 (1), 2020 | 9 | 2020 |
| Optimal vibration image size determination for convolutional neural network based fluid-film rotor-bearing system diagnosis BC Jeon, JH Jung, M Kim, KH Sun, BD Youn Journal of Mechanical Science and Technology 34, 1467-1474, 2020 | 7 | 2020 |
| Evaluation of datum unit for diagnostics of journal-bearing systems B Jeon, J Jung, BD Youn, YW Kim, YC Bae Transactions of the Korean Society of Mechanical Engineers A 39 (8), 801-806, 2015 | 7 | 2015 |
| Anomaly diagnostics for rotor system using statistical analysis of vibration signal B Jeon, J Jung, BD Youn Proceedings of the Korean Society for Noise and Vibration Engineering …, 2013 | 7 | 2013 |
| Noise robust fault diagnosis technique to simultaneously learn classification and denoising JU Ko, JH Jung, M Kim, HB Kong, BD Youn Proceedings of The Korean Soc. of Mech. Eng.(KSME), 165-167, 2018 | 6 | 2018 |
| Label-based, mini-batch combinations study for convolutional neural network based fluid-film bearing rotor system diagnosis JH Jung, M Kim, JU Ko, HB Kong, BD Youn, KH Sun Computers in Industry 133, 103546, 2021 | 5 | 2021 |
