| Understanding and learning discriminant features based on multiattention 1DCNN for wheelset bearing fault diagnosis H Wang, Z Liu, D Peng, Y Qin IEEE Transactions on Industrial Informatics 16 (9), 5735-5745, 2019 | 316 | 2019 |
| A novel deeper one-dimensional CNN with residual learning for fault diagnosis of wheelset bearings in high-speed trains D Peng, Z Liu, H Wang, Y Qin, L Jia Ieee Access 7, 10278-10293, 2018 | 240 | 2018 |
| Multibranch and multiscale CNN for fault diagnosis of wheelset bearings under strong noise and variable load condition D Peng, H Wang, Z Liu, W Zhang, MJ Zuo, J Chen IEEE Transactions on Industrial Informatics 16 (7), 4949-4960, 2020 | 212 | 2020 |
| Attention-guided joint learning CNN with noise robustness for bearing fault diagnosis and vibration signal denoising H Wang, Z Liu, D Peng, Z Cheng ISA transactions 128, 470-484, 2022 | 126 | 2022 |
| Multitask learning based on lightweight 1DCNN for fault diagnosis of wheelset bearings Z Liu, H Wang, J Liu, Y Qin, D Peng IEEE Transactions on Instrumentation and Measurement 70, 1-11, 2020 | 123 | 2020 |
| Feature-level attention-guided multitask CNN for fault diagnosis and working conditions identification of rolling bearing H Wang, Z Liu, D Peng, M Yang, Y Qin IEEE transactions on neural networks and learning systems 33 (9), 4757-4769, 2021 | 95 | 2021 |
| Improved Hilbert–Huang transform with soft sifting stopping criterion and its application to fault diagnosis of wheelset bearings Z Liu, D Peng, MJ Zuo, J Xia, Y Qin ISA transactions 125, 426-444, 2022 | 60 | 2022 |
| Self-supervised signal representation learning for machinery fault diagnosis under limited annotation data H Wang, Z Liu, Y Ge, D Peng Knowledge-Based Systems 239, 107978, 2022 | 53 | 2022 |
| Interpretable convolutional neural network with multilayer wavelet for Noise-Robust Machinery fault diagnosis H Wang, Z Liu, D Peng, MJ Zuo Mechanical Systems and Signal Processing 195, 110314, 2023 | 50 | 2023 |
| ACCUGRAM: A novel approach based on classification to frequency band selection for rotating machinery fault diagnosis Z Liu, Y Jin, MJ Zuo, D Peng ISA transactions 95, 346-357, 2019 | 39 | 2019 |
| Domain adaptation digital twin for rolling element bearing prognostics C Liu, A Ricardo Mauricio, J Qi, D Peng, K Gryllias Online proceedings of PHM2020, 1-10, 2020 | 25 | 2020 |
| RMA-CNN: A residual mixed-domain attention CNN for bearings fault diagnosis and its time-frequency domain interpretability D Peng, H Wang, W Desmet, K Gryllias Journal of Dynamics, Monitoring and Diagnostics 2 (2), 115-132, 2023 | 16 | 2023 |
| Deep unsupervised transfer learning for health status prediction of a fleet of wind turbines with unbalanced data D Peng, C Liu, W Desmet, K Gryllias Proceedings of the Annual Conference of the PHM Society 2021, 2021 | 12 | 2021 |
| An improved 2DCNN with focal loss function for blade icing detection of wind turbines under imbalanced SCADA data D Peng, C Liu, W Desmet, K Gryllias International Conference on Offshore Mechanics and Arctic Engineering 84768 …, 2021 | 8 | 2021 |
| 基于软筛分停止准则的改进经验模态分解及其在旋转机械故障诊断中的应用 彭丹丹， 刘志亮， 靳亚强， 秦勇 机械工程学报 55 (10), 122-132, 2019 | 7 | 2019 |
| Informative frequency band selection based on a new indicator: Accuracy rate Y Jin, Z Liu, D Peng, J Kang, J Ding Journal of Intelligent & Fuzzy Systems 34 (6), 3487-3498, 2018 | 5 | 2018 |
| Blind source separation and identification for speech signals J Yin, Z Liu, Y Jin, D Peng, J Kang 2017 International conference on sensing, diagnostics, prognostics, and …, 2017 | 5 | 2017 |
| A transfer learning-based rolling bearing fault diagnosis across machines D Peng, C Liu, A Ricardo Mauricio, W Desmet, K Gryllias Proceedings of the Annual Conference of the PHM Society 2022 14 (1), 2022 | 4 | 2022 |
| Semi-Supervised CNN-Based SVDD Anomaly Detection for Condition Monitoring of Wind Turbines D Peng, C Liu, W Desmet, K Gryllias International Conference on Offshore Mechanics and Arctic Engineering 86618 …, 2022 | 3 | 2022 |
| Condition Monitoring of Wind Turbines Based on Anomaly Detection Using Deep Support Vector Data Description D Peng, C Liu, W Desmet, K Gryllias Journal of Engineering for Gas Turbines and Power 145 (9), 091009, 2023 | 2 | 2023 |
Zhiliang LiuUniversity of Electronic Science and Technology of China在 uestc.edu.cn 的电子邮件经过验证
