| Data-driven design of robust fault detection system for wind turbines S Yin, G Wang, HR Karimi Mechatronics 24 (4), 298-306, 2014 | 391 | 2014 |
| Data-driven process monitoring based on modified orthogonal projections to latent structures S Yin, G Wang, H Gao IEEE Transactions on Control Systems Technology 24 (4), 1480-1487, 2015 | 258 | 2015 |
| Robust PLS approach for KPI-related prediction and diagnosis against outliers and missing data S Yin, G Wang, X Yang International Journal of Systems Science 45 (7), 1375-1382, 2014 | 196 | 2014 |
| Quality-Related Fault Detection Approach Based on Orthogonal Signal Correction and Modified PLS G Wang, S Yin Industrial Informatics, IEEE Transactions on 11 (2), 398-405, 2015 | 191 | 2015 |
| A LWPR based data-driven fault detection approach for nonlinear process monitoring G Wang, S Yin, O Kaynak IEEE Transactions on Industrial Informatics, 2014 | 116 | 2014 |
| A quality-related fault detection approach based on dynamic least squares for process monitoring J Jiao, H Yu, G Wang IEEE Transactions on Industrial Electronics 63 (4), 2625-2632, 2015 | 99 | 2015 |
| A nonlinear quality-related fault detection approach based on modified kernel partial least squares J Jiao, N Zhao, G Wang, S Yin ISA transactions 66, 275-283, 2017 | 93 | 2017 |
| Quality-related fault detection using linear and nonlinear principal component regression G Wang, H Luo, K Peng Journal of the Franklin Institute 353 (10), 2159-2177, 2016 | 86 | 2016 |
| A kernel least squares based approach for nonlinear quality-related fault detection G Wang, J Jiao IEEE Transactions on Industrial Electronics 64 (4), 3195-3204, 2016 | 78 | 2016 |
| Event triggered trajectory tracking control approach for fully actuated surface vessel J Jiao, G Wang Neurocomputing 182, 267-273, 2016 | 56 | 2016 |
| A kernel direct decomposition-based monitoring approach for nonlinear quality-related fault detection G Wang, J Jiao, S Yin IEEE Transactions on Industrial Informatics 13 (4), 1565-1574, 2016 | 55 | 2016 |
| Quality-related root cause diagnosis based on orthogonal kernel principal component regression and transfer entropy J Jiao, W Zhen, W Zhu, G Wang IEEE Transactions on Industrial Informatics 17 (9), 6347-6356, 2020 | 44 | 2020 |
| Data-driven fault diagnosis for an automobile suspension system by using a clustering based method G Wang, S Yin Journal of the Franklin Institute 351 (6), 3231-3244, 2014 | 43 | 2014 |
| Event driven tracking control algorithm for marine vessel based on backstepping method J Jiao, G Wang Neurocomputing 207, 669-675, 2016 | 34 | 2016 |
| Data‐driven fault‐tolerant control design for wind turbines with robust residual generator G Wang, Z Huang IET Control Theory & Applications 9 (7), 1173-1179, 2015 | 29 | 2015 |
| Chemokine RANTES is upregulated in monocytes from patients with hyperhomocysteinemia1 W Sun, G Wang, Z ZHANG, X ZENG, X Wang Acta Pharmacologica Sinica 26 (11), 1317-1321, 2005 | 24 | 2005 |
| Quality-related fault detection and diagnosis based on total principal component regression model G Wang, J Jiao IEEE Access 6, 10341-10347, 2018 | 23 | 2018 |
| Efficient nonlinear fault diagnosis based on kernel sample equivalent replacement G Wang, J Jiao, S Yin IEEE Transactions on Industrial Informatics 15 (5), 2682-2690, 2018 | 20 | 2018 |
| Data-driven diagnosis of multiple faults in series battery packs based on cross-cell voltage correlation and feature principal components J Xie, H Peng, Z Li, G Wang, X Li IEEE Journal of Emerging and Selected Topics in Power Electronics 11 (1 …, 2021 | 15 | 2021 |
| Voltage correlation-based principal component analysis method for short circuit fault diagnosis of series battery pack G Wang, J Yang, J Jiao IEEE Transactions on Industrial Electronics 70 (9), 9025-9034, 2022 | 14 | 2022 |
Shen YinNorwegian University of Science and TechnologyVerified email at ntnu.no
