2025年

1. Naipeng Li, Xinyu Li, Xiaofei Liu, Xiang Li*, Bin Yang, and Yaguo Lei, Self-data-driven intelligent fault diagnosis of gearboxes with sparse group Lasso, IEEE Transactions on Instrumentation and Measurement, vol. 74, pp. 1-11, 2025.
2. Naipeng Li, Mingyang Wang, Yaguo Lei, Bin Yang*, Xiang Li, and Xiaosheng Si, Remaining useful life prediction of lithium-ion battery with nonparametric degradation modeling and incomplete data, Reliability Engineering & System Safety, 2025, 256: 110721. (中科院一区)
3. Yizhe Yan¹, Feng Hai¹, Bin Wang¹, Wenrui Cao, Mingtao Li, Chaohui Wang*, Naipeng Li*, and Dan Zhao*, Machine learning accelerates high-voltage electrolyte discovery for lithium metal batteries, Energy Storage Materials, 2025, 79: 104312. (中科院一区)
4. Jianhui Yuan, Yaguo Lei*, Bin Yang, Naipeng Li, Xiang Li, Zexun Chen, and Wei Han, A hybrid maintenance strategy for equipment with competitive failure modes: Sudden failure and multi-stage degradation failure, Mechanical Systems and Signal Processing, 2025, 234: 112846. (中科院一区)
5. Bin Yang, Yaguo Lei, Naipeng Li*, Xiang Li, X. Si, and Chuanhai Chen, Balance recovery and collaborative adaptation approach for federated fault diagnosis of inconsistent machine groups, Knowledge-Based Systems, 2025, 317: 113480. (中科院一区)
6. Yaguo Lei*, Huan Liu, Naipeng Li, Junyi Cao, Yuting Qiao, and Hongbo Wang, Condition monitoring and fault diagnosis of industrial robots: A review, Science China Technological Sciences, vol. 68, no. 1, 2024, 68(1): 1110301:1–1110301:25.
7. Bin Yang, Yaguo Lei, Xiang Li*, Naipeng Li, Xiaosheng Si, and Chuanhai Chen, A dynamic barycenter bridging network for federated transfer fault diagnosis in machine groups, Mechanical Systems and Signal Processing, 230, 2025, 230: 112605. (中科院一区)
8. Hongbo Wang, Yuting Qiao, Yaguo Lei, Naipeng Li, Yanxin Zhang, and Junyi Cao*, Asymmetric-dot-pattern fusion fault identification of motor-driven belt transmission system in industrial robots, Measurement, 2025,251: 117267.
9. Pengcheng Xu, Yaguo Lei*, Zidong Wang, Naipeng Li, Xiao Cai, and Ke Feng, A self-data-driven approach for online remaining useful life prediction of machinery using a recursive update strategy, Mechanical Systems and Signal Processing, 2025, 229: 112541. (中科院一区)
10. Jian Yu¹, Bozhao Xiao¹, Jianlong Qiu, Yuanbin Tang, Yanjie Guo, Lei Yang*, Naipeng Li*, and Kai Jiang*, Artificial intelligence-enabled smart monitoring of vancomycin concentration using a droplet-driven triboelectric nanogenerator, Nano Energy, 2025, 136: 110691. (中科院一区)
11. Yaguo Lei*, Xiaofei Liu, Naipeng Li, Xiang Li, and Bin Yang, Owie-Driven spectrum discrepancy impulse reconstruction: An adaptive impulse extraction methodology for rotating machinery, Mechanical Systems and Signal Processing, 2025, 225: 112288. (中科院一区)
12. Yuan Wang, Yaguo Lei*, Naipeng Li, Xiang Li, Bin Yang, Xuanyu Gao, and Xiaofei Liu, Multimodal parallel bilinear co-attention fusion with full-dimensional dynamic wavelet-kernel structure for machinery RUL prediction, Measurement, 2025, 247: 116685.
13. Tao Li¹, Huaitao Shi*, Xiaotian Bai¹, Naipeng Li, and Ke Zhang, Rolling bearing performance assessment with degradation twin modeling considering interdependent fault evolution, Mechanical Systems and Signal Processing, 2025, 224: 112194. (中科院一区)

2024年

14. 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.（中科院一区Top）
15. Xiao Cai, Naipeng Li*, Min Xie. RUL prediction for two-phase degrading systems considering physical damage observations, Reliability Engineering & System Safety, 2024, 244: 109926.（中科院一区Top）
16. Yuan Wang, Lei, Yaguo Lei*, Naipeng Li, Xiang Li, Bin Yang, Multimodal correlation-aware fusion framework for enhanced machinery health prognosis with unlabeled and low-quality data exploitation, IEEE Transactions on Neural Networks and Learning Systems, 2024. (Early Access, 中科院一区Top)
17. Xiaofei Liu, Naipeng Li, Yaguo Lei*, Dong Wang, Qubing Ren, Jinze Jiang, Yuan Wang, Optimal weight impulse extraction: New impulse extraction methodology for incipient gearbox condition monitoring, Mechanical Systems and Signal Processing, 2024, 216: 111449.（中科院一区Top）
18. Yuan Wang, Yaguo Lei*, Naipeng Li, Xuanyu Gao, Xiaofei Liu, Qubing Ren, Jinze Jiang, A multimodal dynamic parameterized bilinear factorized framework for remaining useful life prediction under variational data, Reliability Engineering & System Safety, 2024, 245: 110025.（中科院一区Top）

2023年

19. 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. (中科院一区Top)
20. 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.（中科院1区Top）
21. Xiang Li, Yixiao Xu, Naipeng Li*, Bin Yang, Yaguo Lei. Remaining useful life prediction with partial sensor malfunctions using deep adversarial networks. IEEE/CAA Journal of Automatica Sinica, 2023, 10(1): 121-134.（ESI高被引，中科院1区Top）
22. Yuan Wang, Yaguo Lei*, Naipeng Li, Tao Yan, Xiaosheng Si. Deep multisource parallel bilinear-fusion network for remaining useful life prediction of machinery. Reliability Engineering & System Safety, 2023, 231: 109006. （中科院一区Top）
23. Tao Yan, Yaguo Lei*, Naipeng Li, Liliane Pintelon, Reginald Dewil. Joint optimization of maintenance and spare parts inventory for multi-unit systems with a generalized structure. Journal of Manufacturing Science and Engineering-Transactions of the ASME, 2023, 145(4): 041001.
24. Xiaofei Liu, Yaguo Lei*, Naipeng Li, Xiaosheng Si, Xiang Li. RUL prediction of machinery using convolutional-vector fusion network through multi-feature dynamic weighting. Mechanical Systems and Signal Processing, 2023, 185: 109788.（中科院1区Top）

2022年

25. 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.（中科院1区Top）
26. Tao Yan, Yaguo Lei*, Naipeng Li, Xiaosheng Si, Liliane Pintelon, Reginald Dewil. Online joint replacement-order optimization driven by a nonlinear ensemble remaining useful life prediction method. Mechanical Systems and Signal Processing, 2022, 173:109053.（中科院1区Top）
27. Zhijian Wang*, Xinxin He, Bin Yang, Naipeng Li. Subdomain adaptation transfer learning network for fault diagnosis of roller bearings. IEEE Transactions on Industrial Electronics, 2022, 69(8): 8430-8439.（ESI高被引，中科院1区Top）
28. 雷亚国*, 杨彬, 李乃鹏, 李响, 武通海. 跨设备的机械故障靶向迁移诊断方法. 机械工程学报, 2022, 58(12): 1-9.
29. 韩特, 李彦夫*, 雷亚国, 李乃鹏, 李响. 融合图标签传播和判别特征增强的工业机器人关键部件半监督故障诊断方法. 机械工程学报, 2022, 58(17): 116-124.
30. 贾峰, 李世豪, 沈建军*, 马军星, 李乃鹏. 采用深度迁移学习与自适应加权的滚动轴承故障诊断. 西安交通大学学报, 2022, 56(08): 1-10.

2021年

31. 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.（中科院1区Top）
32. 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.（中科院1区Top）
33. Tao Yan, Yaguo Lei*, Naipeng Li, Biao Wang, Wenting Wang. Degradation modeling and remaining useful life prediction for dependent competing failure processes. Reliability Engineering & System Safety, 2021, 212: 107638. （中科院一区Top）
34. Biao Wang, Yaguo Lei*, Naipeng Li, Wenting Wang. Multiscale convolutional attention network for predicting remaining useful life of machinery. IEEE Transactions on Industrial Electronics, 2021, 68(8): 7496-7504.（ESI热点，中科院1区Top）
35. Zhijian Wang*, Chen Wang, Naipeng Li. Bearing fault diagnosis method based on similarity measure and ensemble learning. Measurement Science and Technology, 2021, 32(5): 055005.
36. Zhijian Wang*, Ningning Yang, Naipeng Li, Wenhua Du, Junyuan Wang. A new fault diagnosis method based on adaptive spectrum mode extraction. Structural Health Monitoring-An International Journal, 2021, 20(6): 3354-3370.（ESI高被引，ESI高被引）
37. Bin Yang, Chi-Guhn Lee, Yaguo Lei*, Naipeng Li, Na Lu. Deep partial transfer learning network: A method to selectively transfer diagnostic knowledge across related machines. Mechanical Systems and Signal Processing, 2021, 156: 107618.（中科院1区Top）
38. Zhijian Wang*, Wenlei Zhao, Wenhua Du, Naipeng Li, Junyuan Wang. Data-driven fault diagnosis method based on the conversion of erosion operation signals into images and convolutional neural network. Process Safety and Environmental Protection, 2021, 149: 591-601.
39. Saibo Xing, Yaguo Lei*, Shuhui Wang, Na Lu, Naipeng Li. A label description space embedded model for zero-shot intelligent diagnosis of mechanical compound faults. Mechanical Systems and Signal Processing, 2021, 162: 108036.（中科院1区Top）
40. 李乃鹏, 蔡潇, 雷亚国*, 徐鹏程, 王彪. 一种融合多传感器数据的数模联动机械剩余寿命预测方法. 机械工程学报, 2021, 57(20): 29-46.
41. 雷亚国*, 许学方, 蔡潇, 李乃鹏, 孔德同, 张勇铭. 面向机械装备健康监测的数据质量保障方法研究. 机械工程学报, 2021, 57(4): 1-9.

2020年

42. Biao Wang, Yaguo Lei*, Naipeng Li, Ningbo Li. A hybrid prognostics approach for estimating remaining useful life of rolling element bearings. IEEE Transactions on Reliability, 2020, 69(1): 401-412.（ESI热点）
43. Bin Yang, Yaguo Lei*, Feng Jia, Naipeng Li, Zhaojun Du. A polynomial kernel induced distance metric to improve deep transfer learning for fault diagnosis of machines. IEEE Transactions on Industrial Electronics, 2020, 67(11): 9747-9757.（ESI高被引，中科院1区Top）
44. Biao Wang, Yaguo Lei*, Tao Yan, Naipeng Li, Liang Guo. Recurrent convolutional neural network: A new framework for remaining useful life prediction of machinery. Neurocomputing, 2020, 379: 117-129. （ESI高被引）
45. Yaguo Lei*, Bin Yang, Xinwei Jiang, Feng Jia, Naipeng Li, Asoke K. Nandi. Applications of machine learning to machine fault diagnosis: A review and roadmap. Mechanical Systems and Signal Processing, 2020, 138: 106587.（ESI热点，中科院1区Top）
46. Tao Yan, Yaguo Lei*, Biao Wang, Tianyu Han, Xiaosheng Si, Naipeng Li. Joint maintenance and spare parts inventory optimization for multi-unit systems considering imperfect maintenance actions. Reliability Engineering and System Safety, 2020, 202: 106994.（中科院1区Top）

2020年以前

47. 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.（中科院1区Top）
48. 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.（ESI高被引，中科院1区Top）
49. 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.（中科院1区Top）
50. 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.（ESI高被引，中科院1区Top）
51. Yaguo Lei*, Naipeng Li, Liang Guo, Ningbo Li, Tao Yan, Jing Lin. Machinery health prognostics: A systematic review from data acquisition to RUL prediction. Mechanical Systems and Signal Processing, 2018, 104: 799-834. （ESI热点，中科院1区Top）
52. Liang Guo, Naipeng Li, Feng Jia, Yaguo Lei, Jing Lin. A recurrent neural network based health indicator for remaining useful life prediction of bearings. Neurocomputing, 2017, 240: 98-109.（ESI高被引）
53. Yaguo Lei*, Naipeng Li, Szymon Gontarz, Jing Lin, Stanislaw Radkowski, Jacek Dybala. A model-based method for remaining useful life prediction of machinery. IEEE Transactions on Reliability, 2016, 65(3): 1314-1326.（ESI高被引）
54. Yaguo Lei*, Naipeng Li, Jing Lin. A new method based on stochastic process models for machine remaining useful life prediction. IEEE Transactions on Instrumentation and Measurement, 2016, 65(12): 2671-2684.
55. Yaguo Lei*, Naipeng Li, Jing Lin, Zhengjia He. Two new features for condition monitoring and fault diagnosis of planetary gearboxes. Journal of Vibration and Control, 2015, 21(4): 755-764.
56. Lang Xue, Naipeng Li, Yaguo Lei*, Ningbo Li. Incipient fault detection for rolling element bearings under varying speed conditions. Materials, 2017, 10(6): 675.
57. Biao Wang, Yaguo Lei*, Naipeng Li, Tao Yan. Deep separable convolutional network for remaining useful life prediction of machinery. Mechanical Systems and Signal Processing, 2019, 134: 106330.（ESI高被引, 中科院1区Top）
58. Zijian Qiao, Yaguo Lei*, Naipeng Li. Applications of stochastic resonance to machinery fault detection: A review and tutorial. Mechanical Systems and Signal Processing, 2019, 122: 502-536.（ESI高被引, 中科院1区Top）
59. Liang Guo, Yaguo Lei*, Naipeng Li, Tao Yan, Ningbo Li. Machinery health indicator construction based on convolutional neural networks considering trend burr. Neurocomputing, 2018, 292: 142-150.
60. Yaguo Lei*, Zongyao Liu, Xionghui Wu, Naipeng Li, Wu Chen, Jing Lin. Health condition identification of multi-stage planetary gearboxes using a mRVM-based method. Mechanical Systems and Signal Processing, 2015, 60-61: 289-300.（中科院1区Top）
61. Liang Guo, Yaguo Lei*, Saibo Xing, Tao Yan, Naipeng Li. Deep convolutional transfer learning network: A new method for intelligent fault diagnosis of machines with unlabeled data. IEEE Transactions on Industrial Electronics, 2019, 66(9): 7316-7325.（ESI热点，IEEE工业电子协会杰出论文奖，中科院1区Top）
62. 雷亚国*, 陈吴, 李乃鹏, 林京. 自适应多核组合相关向量机预测方法及其在机械设备剩余寿命预测中的应用. 机械工程学报, 2016, 52(1): 87-93.
63. 雷亚国*, 孔德同, 李乃鹏, 林京. 自适应总体平均经验模式分解及其在行星齿轮箱故障检测中的应用. 机械工程学报, 2014, 50(3): 64-70.
64. 雷亚国*, 韩天宇, 王彪, 李乃鹏, 闫涛, 杨军. XJTU-SY滚动轴承加速寿命试验数据集解读. 机械工程学报, 2019, 55(16): 1-6.