Naipeng Li
Associate Professor
Xi’an Jiaotong University
No. 28 West Xianning Road
Xi’an Shaanxi, China, 710049
E-mail: naipengli@mail.xjtu.edu.cn
ResearchGate: https://www.researchgate.net/profile/Naipeng-Li-2
English - 李乃鹏 Naipeng Li
Naipeng Li is an associate professor at Xi'an Jiaotong University. He was selected for the 8th China Association for Science and Technology Young Talent Support Program. From 2017 to 2019, he received funding from the China Scholarship Council to study at the Georgia Institute of Technology in the United States. In September 2019, he obtained a Ph.D. in Engineering from Xi'an Jiaotong University. He has been engaged in research in the areas of industrial big data and artificial intelligence, high-end equipment digital twin modeling, mechanical equipment life prediction, and intelligent operation and maintenance. He has published one English monograph with funding from the National Science and Technology Publications Fund, and contributed to the writing of another English monograph published by Elsevier. He has published over 40 high-quality academic papers including 4 ESI hot papers and 5 ESI highly cited papers. He has participated in the development of 4 national standards, and has been granted 25 national invention patents, more than 10 of which have been applied in wind turbines, industrial robots, automobiles, subways etc. His doctoral dissertation was awarded the Outstanding Doctoral Dissertation in Shaanxi Province. He was awarded the First Prize in Natural Science in Shaanxi Province (as the second author), the First Prize in Science and Technology in Higher Education Institutions in Shaanxi Province (as the second author), and the First Prize in Technological Progress of China Huadian Corporation etc.
EDUCATION
2017 – 2019 Visiting Student, Industrial & Systems Engineering, Georgia Institute of Technology, USA
2012 – 2019 Ph.D., Mechanical Engineering, Xi’an Jiaotong University, China
2012 – 2017 B.E., Mechanical Engineering, Shandong Agricultural University, China
EMPLOYMENT
2023 – Pre. Associate Professor, School of Mechanical Engineering, Xi’an Jiaotong University, China
2020 – 2022 Assistant Professor, School of Mechanical Engineering, Xi’an Jiaotong University, China
- Highly Cited Researchers of Clarivate, 2023
- First Prize of Natural Science of Shaanxi Province, 2022
- Youth Talent Promotion Project of China Association for Science and Technology, 2022
- Excellent Doctoral Dissertation of Shaanxi Province, 2022
- First Prize of Science and Technology Progress of China Huadian Corporation LTD, 2018
RESEARCH INTERESTS
1. Industrial Big data and artificial intelligence
2. Intelligent operation and maintenance of wind turbines
3. Robot intelligent diagnosis and treatment
MONOGRAPHS
1. Yaguo Lei, Intelligent Fault Diagnosis and Remaining Useful Life Prediction of Rotating Machinery [M]. Elsevier Butterworth-Heinemann, Oxford, 2016.
2. Yaguo Lei, Naipeng Li, Xiang Li, Big Data-Driven Intelligent Fault Diagnosis and Prognosis for Mechanical Systems [M]. Springer, 2022.
SELECTED PUBLICATIONS
1. Naipeng Li, Mingyang Wang, Yaguo Lei*, Xiaosheng Si, Bin Yang, Xiang Li, A nonparametric degradation modeling method for remaining useful life prediction with fragment data, Reliability Engineering & System Safety, 2024, 249: 110224.
2. Naipeng Li, Yaguo Lei*, Xiaofei Liu, Tao Yan, Pengcheng Xu, Machinery health prognostics with multimodel fusion degradation modeling, IEEE Transactions on Industrial Electronics, 2023, 70(11): 11764-11773.
3. Naipeng Li, Yaguo Lei, Xiang Li*, Xiaofei Liu, Bin Yang, A new nonparametric degradation modeling method for truncated degradation signals by axis rotation, Mechanical Systems and Signal Processing, 2023, 192: 110213.
4. Naipeng Li, Pengcheng Xu, Yaguo Lei*, Xiao Cai, Detong Kong, A self-data-driven method for remaining useful life prediction of wind turbines considering continuously varying speeds. Mechanical Systems and Signal Processing, 2022, 165: 108315.
5. Naipeng Li, Yaguo Lei*, Nagi Gebraeel, Zhijian Wang, Xiao Cai, Pengcheng Xu, Biao Wang. Multi-sensor data-driven remaining useful life prediction of semi-observable systems. IEEE Transactions on Industrial Electronics, 2021, 68(11): 11482-91.
6. Naipeng Li, Nagi Gebraeel, Yaguo Lei*, Xiaolei Fang, Xiao Cai, Tao Yan. Remaining useful life prediction based on a multi-sensor data fusion model. Reliability Engineering & System Safety, 2021, 208: 107249.
7. Naipeng Li, Nagi Gebraeel, Yaguo Lei*, Linkan Bian, Xiaosheng Si. Remaining useful life prediction of machinery under time-varying operating conditions based on a two-factor state-space model. Reliability Engineering & System Safety, 2019, 186: 88-100.
8. Naipeng Li, Yaguo Lei*, Tao Yan, Ningbo Li, Tianyu Han. A Wiener-process-model-based method for remaining useful life prediction considering unit-to-unit variability. IEEE Transactions on Industrial Electronics, 2019, 66(3): 2092-2101.
9. Naipeng Li, Yaguo Lei*, Liang Guo, Tao Yan, Jing Lin. Remaining useful life prediction based on a general expression of stochastic process models. IEEE Transactions on Industrial Electronics, 2017, 64(7): 5709-5718.
10. Naipeng Li, Yaguo Lei*, Jing Lin, Steven X. An improved exponential model for predicting remaining useful life of rolling element bearings. IEEE Transactions on Industrial Electronics, 2015, 62(12): 7762-7773.
