姓 名：刘超
技术职务：助理研究员
办公电话：
通讯地址：清华大学能源与动力工程系燃气轮机研究所，北京 100084
电子邮件：cliu5@tsinghua.edu.cn
个人主页：https://cliu08.wordpress.com/
教育背景2008.9-2013.7 清华大学热能工程系动力工程及工程热物理博士
2004.9-2008.7 华中科技大学能源与动力工程学院 热能与动力工程学士
工作履历2017.8-至今清华大学，能源与动力工程系 助理研究员
2015.8-2017.8 IowaState University, Department of Mechanical Engineering, Postdoctoral Researcher
2013.7-2015.7 清华大学，机械工程系，博士后
研究领域·旋转机械结构动力学、失效机理与预防；
·动力系统预测诊断与健康管理；
·信息物理系统(CPS)数据挖掘、时间序列分析、概率图模型与机器学习
奖励与荣誉2013年清华大学优秀博士学位论文
2010年IEEEPHMBestPaperAward
学术成果 期刊论文
18. Yang, W., Liu, C., and Jiang, D. (2018). An unsupervised spatiotemporal graphical modeling approach for wind turbine condition monitoring. Renewable Energy, 127:230 – 241
17. Liu, C., Akintayo, A., Jiang, Z., Henze, G. P., and Sarkar, S. (2018). Multivariate exploration of non-intrusive load monitoring via spatiotemporal pattern network. Applied Energy, 211:1106–1122
16. Huang, T., Liu, C., Sharma, A., and Sarkar, S. (2018). Traffic system anomaly detection using spatiotemporal pattern networks. International Journal of Prognostics and Health Management, 9:003
15. Jiang, Z., Liu, C., Akintayo, A., Henze, G. P., and Sarkar, S. (2017). Energy prediction using spatiotemporal pattern networks. Applied Energy, 206:1022–1039
14. Liu, C., Ghosal, S., Jiang, Z., and Sarkar, S. (2017). An unsupervised anomaly detection approach using energy-based spatiotemporal graphical modeling. Cyber-Physical Systems, pages 1–37
13. Liu, C. and Jiang, D. (2017). Influence analysis of nonlinear stress–strain behavior in pulverizing wheel of fan mill. Journal of Failure Analysis and Prevention, 17(3):571–580
12. Liu, C., Gong, Y., Laflamme, S., Phares, B., and Sarkar, S. (2017). Bridge damage detection using spatiotemporal patterns extracted from dense sensor network. Measurement Science and Technology, 28(1):014011
11. Liu, C. and Jiang, D. (2017). Dynamics of slant cracked rotor for steam turbine generator system. Journal of Engineering for Gas Turbines and Power, 139(6):062502
10. Xie, X., Zhang, C., Liu, H., Liu, C., Jiang, D., and Zhou, B. (2016). Continuous-mass-model-based mechanical and electrical co-simulation of SSR and its application to a practical shaft failure event. IEEE Transactions on Power Systems, 31(6):5172–5180
9. Liu, C., Jiang, D., and Chu, F. (2015). Influence of alternating loads on nonlinear vibration characteristics of cracked blade in rotor system. Journal of Sound and Vibration, 353:205–219
8. Liu, C. and Jiang, D. (2014). Crack modeling of rotating blades with cracked hexahedral finite element method. Mechanical Systems and Signal Processing, 46(2):406–423
7. Liu, C., Jiang, D., and Chen, J. (2014). Coupled torsional vibration and fatigue damage of turbine generator due to grid disturbance. Journal of Engineering for Gas Turbines and Power, 136(6):062501
6. Liu, C., Jiang, D., and Yang, W. (2014). Global geometric similarity scheme for feature selection in fault diagnosis. Expert Systems with Applications, 41(8):3585–3595
5. Liu, C., Jiang, D., Chu, F., and Chen, J. (2014). Crack cause analysis of pulverizing wheel in fan mill of 600mw steam turbine unit. Engineering Failure Analysis, 42:60–73
4. Liu, C., Jiang, D., Chen, J., and Chen, J. (2012). Torsional vibration and fatigue evaluation in repairing the worn shafting of the steam turbine. Engineering Failure Analysis, 26:1–11
3. An, X., Jiang, D., Zhao, M., and Liu, C. (2012). Short-term prediction of wind power using EMD and chaotic theory. Communications in Nonlinear Science and Numerical Simulation, 17(2):1036–1042
2. An, X., Jiang, D., Liu, C., and Zhao, M. (2011). Wind farm power prediction based on wavelet decomposition and chaotic time series. Expert Systems with Applications, 38(9):11280–11285
1. Jiang, D. and Liu, C. (2011). Machine condition classification using deterioration feature extraction and anomaly determination. IEEE Transactions on Reliability, 60(1):41–48
会议论文
22. Liu, C., Jiang, Z., Akintayo, A., Henze, G., and Sarkar, S. (2018). Building energy disaggregation using spatiotemporal pattern network. In Proceedings of American Conference
21. Huang, T., Liu, C., Sharma, A., and Sarkar, S. (2017). Traffic system anomaly detection using spatiotemporal pattern networks. In the 2nd ACM SIGKDD Workshop on Machine Learning for Prognostics & Health Management
20. Wu, L., Liu, C., Huang, T., Sharma, A., and Sarkar, S. (2017). Traffic sensor health monitoring using spatiotemporal graphical modeling. In the 2nd ACM SIGKDD Workshop on Machine Learning for Prognostics & Health Management
19. Liu, C., Lore, K. G., and Sarkar, S. (2017). Data-driven root-cause analysis for distributed system anomalies. In Decision and Control (CDC), 2017 IEEE 56th Annual Conference on, pages 5745–5750. IEEE
18. Liu, C., Huang, B., Zhao, M., Sarkar, S., Vaidya, U., and Sharma, A. (2016). Data driven exploration of traffic network system dynamics using high resolution probe data. In Decision and Control (CDC), 2016 IEEE 55th Conference on, pages 7629–7634. IEEE
17. Liu, C., Gong, Y., Laflamme, S., Phares, B., and Sarkar, S. (2016). Damage detection of bridge network with spatiotemporal pattern network. In Proceedings of ASME 2016 Dynamic Systems and Control Conference, DSCC 2016. ASME
16. Liu, C., Ghosal, S., Jiang, Z., and Sarkar, S. (2016). An unsupervised spatiotemporal graphical modeling approach to anomaly detection in distributed cps. In 2016 ACM/IEEE 7th International Conference on Cyber-Physical Systems (ICCPS), pages 1–10. IEEE
15. Ghosal, S., Liu, C., Passe, U., He, S., and Sarkar, S. (2016). Data-driven persistent monitoring of indoor air systems. In IAQ 2016. Ashrae
14. Liu, C., Jiang, D., and Yang, W. (2015). Feature extraction in machine degradation with variational mode decomposition. In Proceedings of MFPT 2015. MFPT
13. Liu, C., Jiang, D., and Chu, F. (2014). Failure analysis of fan mill in thermal power plant. In Proceedings of MFPT 2014. MFPT
12. Liu, C., Jiang, D., and Chu, F. (2014). Remaining useful life prediction of crack growth with bayesian inference. In Proceedings of COMADEM 2014
11. Chen, J., Jiang, D., and Liu, C. (2013). Identification of multi-concurrent fault in a steam turbine rotor system using model-based method. In ASME Turbo Expo 2013: Turbine Technical Conference and Exposition, page V07AT29A010. ASME
10. Liu, C. and Jiang, D. (2013). Experimental study on lateral and torsional vibration of cracked rotor with torsional excitation. In ASME Turbo Expo 2013: Turbine Technical Conference and Exposition, page V07AT29A011. ASME
9. Liu, C. and Jiang, D. (2012). Improved blade tip timing in blade vibration monitoring with torsional vibration of the rotor. In Journal of Physics: Conference Series, volume 364, page 012136. IOP Publishing
8. Jiang, D. and Liu, C. (2011). Crack growth prediction of the steam turbine generator shaft. In Journal of Physics: Conference Series, volume 305, page 012023. IOP Publishing
7. Jiang, D., Liu, C., An, X., and Chen, J. (2010). Study on stress and strain for fatigue cumulation evaluation in turbine generator shafts due to torsional vibration. In Proceedings of COMADEM 2010–Advances in Maintenance and Condition Diagnosis Technologies Towards Sustainable Society, pages 441–447
6. Jiang, D. and Liu, C. (2010). Condition classification and tendency prediction for prognostics using feature extraction and reconstruction. In 2010 Prognostics and System Health Management Conference, pages 1–7. IEEE
5. Liu, C. and Jiang, D. (2010). Fatigue damage evaluation of turbine generator due to multi-mode subsynchronous oscillation. In ASME 2010 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference, pages 711–718. ASME
4. Liu, C., Jiang, D., and Chen, J. (2010). Vibration characteristics on a wind turbine rotor using modal and harmonic analysis of fem. In 2010 World Non-Grid-Connected Wind Power and Energy Conference, pages 1–5. IEEE
3. Jiang, D., Liu, C., and Li, S. (2010). Application of support vector machine on deterioration condition classification and prediction of prognostics. In CM 2010 and MFPT 2010
2. Liu, C., Jiang, D., and Hong, L. (2010). The strength design and check of turbine generator based on FEA and fatigue evaluation. Advanced Materials Research, 97:3165–3168
1. Jiang, D., Liu, C., and Chen, J. (2010). Study on torsional vibration of turbine generator shafts owning to network disturbance. In the 8th IFToMM on Rotordynamics