| Deep learning based approach for bearing fault diagnosis M He, D He IEEE Transactions on Industry Applications 53 (3), 3057-3065, 2017 | 482 | 2017 |
| Using deep learning-based approach to predict remaining useful life of rotating components J Deutsch, D He IEEE Transactions on Systems, Man, and Cybernetics: Systems 48 (1), 11-20, 2017 | 461 | 2017 |
| A segmental hidden semi-Markov model (HSMM)-based diagnostics and prognostics framework and methodology M Dong, D He Mechanical systems and signal processing 21 (5), 2248-2266, 2007 | 451 | 2007 |
| Hidden semi-Markov model-based methodology for multi-sensor equipment health diagnosis and prognosis M Dong, D He European Journal of Operational Research 178 (3), 858-878, 2007 | 379 | 2007 |
| A directed acyclic graph network combined with CNN and LSTM for remaining useful life prediction J Li, X Li, D He IEEE Access 7, 75464-75475, 2019 | 264 | 2019 |
| Rotational machine health monitoring and fault detection using EMD-based acoustic emission feature quantification R Li, D He IEEE Transactions on Instrumentation and Measurement 61 (4), 990-1001, 2012 | 230 | 2012 |
| PM2. 5 concentration prediction using hidden semi-Markov model-based times series data mining M Dong, D Yang, Y Kuang, D He, S Erdal, D Kenski Expert Systems with Applications 36 (5), 9046-9055, 2009 | 170 | 2009 |
| Plastic bearing fault diagnosis based on a two-step data mining approach D He, R Li, J Zhu IEEE Transactions on Industrial Electronics 60 (8), 3429-3440, 2012 | 162 | 2012 |
| Lithium-ion battery life prognostic health management system using particle filtering framework M Dalal, J Ma, D He Proceedings of the Institution of Mechanical Engineers, Part O: Journal of …, 2011 | 150 | 2011 |
| Gearbox tooth cut fault diagnostics using acoustic emission and vibration sensors—A comparative study Y Qu, D He, J Yoon, B Van Hecke, E Bechhoefer, J Zhu Sensors 14 (1), 1372-1393, 2014 | 149 | 2014 |
| Design of assembly systems for modular products DW He, A Kusiak IEEE Transactions on Robotics and Automation 13 (5), 646-655, 1997 | 146 | 1997 |
| Low speed bearing fault diagnosis using acoustic emission sensors B Van Hecke, J Yoon, D He Applied Acoustics 105, 35-44, 2016 | 143 | 2016 |
| Lubrication oil condition monitoring and remaining useful life prediction with particle filtering J Zhu, JM Yoon, D He, Y Qu, E Bechhoefer International Journal of Prognostics and Health Management 4, 124-138, 2013 | 141 | 2013 |
| Design of double-and triple-sampling X-bar control charts using genetic algorithms D He, A Grigoryan, M Sigh International Journal of Production Research 40 (6), 1387-1404, 2002 | 138 | 2002 |
| Survey of lubrication oil condition monitoring, diagnostics, and prognostics techniques and systems J Zhu, D He, E Bechhoefer Journal of chemical science and technology 2 (3), 100-115, 2013 | 136 | 2013 |
| Equipment health diagnosis and prognosis using hidden semi-Markov models M Dong, D He, P Banerjee, J Keller The International Journal of Advanced Manufacturing Technology 30, 738-749, 2006 | 133 | 2006 |
| Online particle‐contaminated lubrication oil condition monitoring and remaining useful life prediction for wind turbines J Zhu, JM Yoon, D He, E Bechhoefer Wind Energy 18 (6), 1131-1149, 2015 | 124 | 2015 |
| Analysis of sequential failures for assessment of reliability and safety of manufacturing systems A Adamyan, D He Reliability Engineering & System Safety 76 (3), 227-236, 2002 | 119 | 2002 |
| Semi-supervised gear fault diagnosis using raw vibration signal based on deep learning LI Xueyi, LI Jialin, QU Yongzhi, HE David Chinese Journal of Aeronautics 33 (2), 418-426, 2020 | 113 | 2020 |
| Fault features extraction for bearing prognostics R Li, P Sopon, D He Journal of Intelligent Manufacturing 23, 313-321, 2012 | 105 | 2012 |
