| A physics-informed deep learning approach for bearing fault detection S Shen, H Lu, M Sadoughi, C Hu, V Nemani, A Thelen, K Webster, M Darr, ... Engineering Applications of Artificial Intelligence 103, 104295, 2021 | 151 | 2021 |
| Joint training of a predictor network and a generative adversarial network for time series forecasting: A case study of bearing prognostics H Lu, V Barzegar, VP Nemani, C Hu, S Laflamme, AT Zimmerman Expert Systems with Applications 203, 117415, 2022 | 27 | 2022 |
| Ensembles of probabilistic LSTM predictors and correctors for bearing prognostics using industrial standards VP Nemani, H Lu, A Thelen, C Hu, AT Zimmerman Neurocomputing 491, 575-596, 2022 | 26 | 2022 |
| A physics-informed feature weighting method for bearing fault diagnostics H Lu, VP Nemani, V Barzegar, C Allen, C Hu, S Laflamme, S Sarkar, ... Mechanical Systems and Signal Processing 191, 110171, 2023 | 25 | 2023 |
| A deep learning approach for failure prognostics of rolling element bearings M Sadoughi, H Lu, C Hu 2019 IEEE International Conference on Prognostics and Health Management …, 2019 | 15 | 2019 |
| GAN-LSTM predictor for failure prognostics of rolling element bearings H Lu, V Barzegar, VP Nemani, C Hu, S Laflamme, AT Zimmerman 2021 IEEE International Conference on Prognostics and Health Management …, 2021 | 14 | 2021 |
| Federated learning with uncertainty-based client clustering for fleet-wide fault diagnosis H Lu, A Thelen, O Fink, C Hu, S Laflamme Mechanical Systems and Signal Processing 210, 111068, 2024 | 5 | 2024 |
| Fault diagnosis of rolling element bearings on low-cost and scalable IIoT platform HAO LU, M SADOUGHI, AT ZIMMERMAN, C HU Structural Health Monitoring 2019, 2019 | 4 | 2019 |
| An interpretable deep learning method for bearing fault diagnosis H Lu, AM Bray, C Hu, AT Zimmerman, H Xu arXiv preprint arXiv:2308.10292, 2023 | 1 | 2023 |
