Naipeng Li
Orcid: 0000-0003-0678-8161
According to our database1,
Naipeng Li
authored at least 31 papers
between 2013 and 2024.
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Bibliography
2024
An Optimal-Subdomain Generalization Method for Remaining Useful Life Prediction of Machinery Under Time-Varying Operation Conditions.
IEEE Trans. Ind. Informatics, April, 2024
Label Recovery and Trajectory Designable Network for Transfer Fault Diagnosis of Machines With Incorrect Annotation.
IEEE CAA J. Autom. Sinica, April, 2024
Dynamic Vision Enabled Contactless Cross-Domain Machine Fault Diagnosis with Neuromorphic Computing.
IEEE CAA J. Autom. Sinica, March, 2024
IEEE Trans. Ind. Informatics, January, 2024
2023
IEEE Trans. Ind. Electron., November, 2023
Deep multisource parallel bilinear-fusion network for remaining useful life prediction of machinery.
Reliab. Eng. Syst. Saf., 2023
Remaining Useful Life Prediction With Partial Sensor Malfunctions Using Deep Adversarial Networks.
IEEE CAA J. Autom. Sinica, 2023
Non-Contact Machine Vibration Sensing and Fault Diagnosis Method Based on Event Camera.
Proceedings of the CAA Symposium on Fault Detection, 2023
2022
Subdomain Adaptation Transfer Learning Network for Fault Diagnosis of Roller Bearings.
IEEE Trans. Ind. Electron., 2022
2021
Multiscale Convolutional Attention Network for Predicting Remaining Useful Life of Machinery.
IEEE Trans. Ind. Electron., 2021
Multi-Sensor Data-Driven Remaining Useful Life Prediction of Semi-Observable Systems.
IEEE Trans. Ind. Electron., 2021
Degradation modeling and remaining useful life prediction for dependent competing failure processes.
Reliab. Eng. Syst. Saf., 2021
Reliab. Eng. Syst. Saf., 2021
Proceedings of the IEEE Global Communications Conference, 2021
2020
A Hybrid Prognostics Approach for Estimating Remaining Useful Life of Rolling Element Bearings.
IEEE Trans. Reliab., 2020
A Polynomial Kernel Induced Distance Metric to Improve Deep Transfer Learning for Fault Diagnosis of Machines.
IEEE Trans. Ind. Electron., 2020
Joint maintenance and spare parts inventory optimization for multi-unit systems considering imperfect maintenance actions.
Reliab. Eng. Syst. Saf., 2020
Recurrent convolutional neural network: A new framework for remaining useful life prediction of machinery.
Neurocomputing, 2020
2019
A Wiener-Process-Model-Based Method for Remaining Useful Life Prediction Considering Unit-to-Unit Variability.
IEEE Trans. Ind. Electron., 2019
Deep Convolutional Transfer Learning Network: A New Method for Intelligent Fault Diagnosis of Machines With Unlabeled Data.
IEEE Trans. Ind. Electron., 2019
Remaining useful life prediction of machinery under time-varying operating conditions based on a two-factor state-space model.
Reliab. Eng. Syst. Saf., 2019
2018
Machinery health indicator construction based on convolutional neural networks considering trend burr.
Neurocomputing, 2018
Remaining Useful Life Prediction of Machinery Subjected to Two-Phase Degradation Process.
Proceedings of the 2018 IEEE International Conference on Prognostics and Health Management, 2018
2017
Remaining Useful Life Prediction Based on a General Expression of Stochastic Process Models.
IEEE Trans. Ind. Electron., 2017
A recurrent neural network based health indicator for remaining useful life prediction of bearings.
Neurocomputing, 2017
An improved fusion prognostics method for remaining useful life prediction of bearings.
Proceedings of the 2017 IEEE International Conference on Prognostics and Health Management, 2017
Proceedings of the 2017 IEEE International Conference on Prognostics and Health Management, 2017
2016
IEEE Trans. Reliab., 2016
A New Method Based on Stochastic Process Models for Machine Remaining Useful Life Prediction.
IEEE Trans. Instrum. Meas., 2016
2015
An Improved Exponential Model for Predicting Remaining Useful Life of Rolling Element Bearings.
IEEE Trans. Ind. Electron., 2015
2013
Fault Diagnosis of Rotating Machinery Based on an Adaptive Ensemble Empirical Mode Decomposition.
Sensors, 2013