| Introduction to cyber manufacturing J Lee, B Bagheri, C Jin Manufacturing Letters 8, 11-15, 2016 | 254 | 2016 |
| Wind turbine performance degradation assessment based on a novel similarity metric for machine performance curves X Jia, C Jin, M Buzza, W Wang, J Lee Renewable Energy 99, 1191–1201, 2016 | 137 | 2016 |
| Cyber physical systems for predictive production systems J Lee, C Jin, B Bagheri Production Engineering, 1-11, 2017 | 121 | 2017 |
| Introduction to data-driven methodologies for prognostics and health management J Lee, C Jin, Z Liu, H Davari Ardakani Probabilistic prognostics and health management of energy systems, 9-32, 2017 | 70 | 2017 |
| Investigation on the kurtosis filter and the derivation of convolutional sparse filter for impulsive signature enhancement X Jia, M Zhao, Y Di, C Jin, J Lee Journal of Sound and Vibration 386, 433-448, 2017 | 66 | 2017 |
| A deviation based assessment methodology for multiple machine health patterns classification and fault detection X Jia, C Jin, M Buzza, Y Di, D Siegel, J Lee Mechanical Systems and Signal Processing 99, 244–261, 2018 | 53 | 2018 |
| Review of data-driven prognostics and health management techniques: lessions learned from PHM data challenge competitions B Huang, Y Di, C Jin, J Lee Machine Failure Prevention Technology 2017, 1-17, 2017 | 39 | 2017 |
| Industrial AI enabled prognostics for high-speed railway systems Z Liu, C Jin, W Jin, J Lee, Z Zhang, C Peng, G Xu 2018 IEEE international conference on prognostics and health management …, 2018 | 35 | 2018 |
| A comprehensive framework of factory-to-factory dynamic fleet-level prognostics and operation management for geographically distributed assets C Jin, D Djurdjanovic, HD Ardakani, K Wang, M Buzza, B Begheri, ... 2015 ieee international conference on automation science and engineering …, 2015 | 34 | 2015 |
| Fault prediction of power electronics modules and systems under complex working conditions Y Di, C Jin, B Bagheri, Z Shi, HD Ardakani, Z Tang, J Lee Computers in Industry 97, 1-9, 2018 | 31 | 2018 |
| Predictive big data analytics and cyber physical systems for TES systems J Lee, C Jin, Z Liu Advances in Through-life Engineering Services, 97-112, 2017 | 31 | 2017 |
| CPS-enabled worry-free industrial applications W Jin, Z Liu, Z Shi, C Jin, J Lee 2017 Prognostics and System Health Management Conference (PHM-Harbin), 1-7, 2017 | 27 | 2017 |
| A sequential process monitoring approach using hidden Markov model for unobservable process drift C Jin University of Cincinnati, 2015 | 14 | 2015 |
| Envelope Analysis on Vibration Signals for Stator Winding Fault Early Detection in 3-Phase Induction Motors C Jin, AP Ompusunggu, Z Liu, HD Ardakani, F Petré, J Lee INTERNATIONAL JOURNAL OF PROGNOSTICS AND HEALTH MANAGEMENT 6, 2015 | 14 | 2015 |
| A vibration-based approach for diesel engine fault diagnosis C Jin, W Zhao, Z Liu, J Lee, X He 2014 International Conference on Prognostics and Health Management, 1-9, 2014 | 14 | 2014 |
| A Vibration-Based Approach for Stator Winding Fault Diagnosis of Induction Motors: Application of Envelope Analysis C Jin, AP Ompusunggu, Z Liu, HD Ardakani, F Petré, J Lee Annual Conference of the Prognostics and Health Management Society 2014 5, 2014 | 8 | 2014 |
| Winding fault diagnosis of a 3-phase induction motor powered by frequency-inverter drive using the current and voltage signals AP Ompusunggu, Z Liu, HD Ardakani, C Jin, F Petré, J Lee Proceedings of the 14th Mechatronics Forum International Conference, 16-18, 2014 | 5 | 2014 |
| IAI DevOps: A Systematic Framework for Prognostic Model Lifecycle Management Z Guo, T Bao, W Wu, C Jin, J Lee 2019 Prognostics and System Health Management Conference (PHM-Qingdao), 1-6, 2019 | 2 | 2019 |
| Methodology on Exact Extraction of Time Series Features for Robust Prognostics and Health Monitoring C Jin University of Cincinnati, 2017 | 1 | 2017 |
| Dynamic Condition based Feature Extraction Strategy for Machine Health Monitoring Applications HA Kao, C Jin, L Zongchang, S Yang, Z Shi Machinery Failure Prevention Technology (MFPT) 2014, 2014 | | 2014 |
Jay LeeClark Distingusihed Professor and Director of Industrial AI, University of Maryland College Park在 umd.edu 的电子邮件经过验证
