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2020 – today
- 2024
[j32]Bin Yang
, Yaguo Lei, Xiang Li, Naipeng Li:
Targeted transfer learning through distribution barycenter medium for intelligent fault diagnosis of machines with data decentralization. Expert Syst. Appl. 244: 122997 (2024)- [j31]Xinrui Chen, Xiang Li, Shupeng Yu, Yaguo Lei, Naipeng Li, Bin Yang:
Dynamic Vision Enabled Contactless Cross-Domain Machine Fault Diagnosis with Neuromorphic Computing. IEEE CAA J. Autom. Sinica 11(3): 788-790 (2024) - [j30]Bin Yang, Yaguo Lei, Xiang Li, Naipeng Li, Asoke K. Nandi:
Label Recovery and Trajectory Designable Network for Transfer Fault Diagnosis of Machines With Incorrect Annotation. IEEE CAA J. Autom. Sinica 11(4): 932-945 (2024) - [j29]Xiang Li, Shupeng Yu, Yaguo Lei, Naipeng Li, Bin Yang:
Dynamic Vision-Based Machinery Fault Diagnosis with Cross-Modality Feature Alignment. IEEE CAA J. Autom. Sinica 11(10): 2068-2081 (2024) - [j28]Xiao Cai, Naipeng Li, Min Xie:
RUL prediction for two-phase degrading systems considering physical damage observations. Reliab. Eng. Syst. Saf. 244: 109926 (2024) - [j27]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. Reliab. Eng. Syst. Saf. 245: 110025 (2024) - [j26]Xiao-Sheng Si, Huiqin Li, Zhengxin Zhang, Naipeng Li:
A Wiener-process-inspired semi-stochastic filtering approach for prognostics. Reliab. Eng. Syst. Saf. 249: 110200 (2024) - [j25]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. Reliab. Eng. Syst. Saf. 249: 110224 (2024) - [j24]Xiang Li, Shupeng Yu, Yaguo Lei, Naipeng Li, Bin Yang:
Intelligent Machinery Fault Diagnosis With Event-Based Camera. IEEE Trans. Ind. Informatics 20(1): 380-389 (2024) - [j23]Xiaofei Liu, Yaguo Lei, Naipeng Li, Xiang Li, Bin Yang:
An Optimal-Subdomain Generalization Method for Remaining Useful Life Prediction of Machinery Under Time-Varying Operation Conditions. IEEE Trans. Ind. Informatics 20(4): 6177-6186 (2024) - 2023
- [j22]Xiang Li, Yixiao Xu, Naipeng Li, Bin Yang, Yaguo Lei:
Remaining Useful Life Prediction With Partial Sensor Malfunctions Using Deep Adversarial Networks. IEEE CAA J. Autom. Sinica 10(1): 121-134 (2023) - [j21]Yuan Wang, Yaguo Lei, Naipeng Li, Tao Yan, Xiaosheng Si:
Deep multisource parallel bilinear-fusion network for remaining useful life prediction of machinery. Reliab. Eng. Syst. Saf. 231: 109006 (2023) - [j20]Naipeng Li, Yaguo Lei, Xiaofei Liu, Tao Yan, Pengcheng Xu:
Machinery Health Prognostics With Multimodel Fusion Degradation Modeling. IEEE Trans. Ind. Electron. 70(11): 11764-11773 (2023) - [c5]Ruiyi Guang, Xiang Li, Yaguo Lei, Naipeng Li, Bin Yang:
Non-Contact Machine Vibration Sensing and Fault Diagnosis Method Based on Event Camera. SAFEPROCESS 2023: 1-5 - 2022
- [j19]Zhijian Wang, Xinxin He, Bin Yang, Naipeng Li:
Subdomain Adaptation Transfer Learning Network for Fault Diagnosis of Roller Bearings. IEEE Trans. Ind. Electron. 69(8): 8430-8439 (2022) - 2021
- [j18]Naipeng Li, Nagi Gebraeel, Yaguo Lei, Xiaolei Fang, Xiao Cai, Tao Yan:
Remaining useful life prediction based on a multi-sensor data fusion model. Reliab. Eng. Syst. Saf. 208: 107249 (2021) - [j17]Tao Yan, Yaguo Lei, Naipeng Li, Biao Wang, Wenting Wang:
Degradation modeling and remaining useful life prediction for dependent competing failure processes. Reliab. Eng. Syst. Saf. 212: 107638 (2021) - [j16]Biao Wang, Yaguo Lei, Naipeng Li, Wenting Wang:
Multiscale Convolutional Attention Network for Predicting Remaining Useful Life of Machinery. IEEE Trans. Ind. Electron. 68(8): 7496-7504 (2021) - [j15]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 Trans. Ind. Electron. 68(11): 11482-11491 (2021) - [c4]Jingjing Yang, Yuchun Guo, Yishuai Chen, Yongxiang Zhao, Naipeng Li:
Vulnerability Analysis of Road Network under Information Pollution Attacks in VANET. GLOBECOM 2021: 1-6 - 2020
- [j14]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 379: 117-129 (2020) - [j13]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. Reliab. Eng. Syst. Saf. 202: 106994 (2020) - [j12]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 Trans. Ind. Electron. 67(11): 9747-9757 (2020) - [j11]Biao Wang, Yaguo Lei, Naipeng Li, Ningbo Li:
A Hybrid Prognostics Approach for Estimating Remaining Useful Life of Rolling Element Bearings. IEEE Trans. Reliab. 69(1): 401-412 (2020)
2010 – 2019
- 2019
- [j10]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. Reliab. Eng. Syst. Saf. 186: 88-100 (2019) - [j9]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 Trans. Ind. Electron. 66(3): 2092-2101 (2019) - [j8]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 Trans. Ind. Electron. 66(9): 7316-7325 (2019) - 2018
- [j7]Liang Guo, Yaguo Lei, Naipeng Li, Tao Yan, Ningbo Li:
Machinery health indicator construction based on convolutional neural networks considering trend burr. Neurocomputing 292: 142-150 (2018) - [c3]Tao Yan, Yaguo Lei, Naipeng Li:
Remaining Useful Life Prediction of Machinery Subjected to Two-Phase Degradation Process. ICPHM 2018: 1-6 - 2017
- [j6]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 240: 98-109 (2017) - [j5]Naipeng Li, Yaguo Lei, Liang Guo, Tao Yan, Jing Lin:
Remaining Useful Life Prediction Based on a General Expression of Stochastic Process Models. IEEE Trans. Ind. Electron. 64(7): 5709-5718 (2017) - [c2]Biao Wang, Yaguo Lei, Naipeng Li, Jing Lin:
An improved fusion prognostics method for remaining useful life prediction of bearings. ICPHM 2017: 18-24 - [c1]Naipeng Li, Yaguo Lei, Ningbo Li, Jing Lin:
Machine remaining useful life prediction considering unit-to-unit variability. ICPHM 2017: 103-108 - 2016
- [j4]Yaguo Lei, Naipeng Li, Jing Lin:
A New Method Based on Stochastic Process Models for Machine Remaining Useful Life Prediction. IEEE Trans. Instrum. Meas. 65(12): 2671-2684 (2016) - [j3]Yaguo Lei, Naipeng Li, Szymon Gontarz, Jing Lin, Stanislaw Radkowski, Jacek Dybala:
A Model-Based Method for Remaining Useful Life Prediction of Machinery. IEEE Trans. Reliab. 65(3): 1314-1326 (2016) - 2015
- [j2]Naipeng Li, Yaguo Lei, Jing Lin, Steven X. Ding:
An Improved Exponential Model for Predicting Remaining Useful Life of Rolling Element Bearings. IEEE Trans. Ind. Electron. 62(12): 7762-7773 (2015) - 2013
- [j1]Yaguo Lei, Naipeng Li, Jing Lin, Sizhe Wang:
Fault Diagnosis of Rotating Machinery Based on an Adaptive Ensemble Empirical Mode Decomposition. Sensors 13(12): 16950-16964 (2013)
Coauthor Index
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