| A novel statistical time-frequency analysis for rotating machine condition monitoring T Wang, G Lu, P Yan IEEE Transactions on Industrial Electronics 67 (1), 531-541, 2019 | 78 | 2019 |
| Temporal-spatio graph based spectrum analysis for bearing fault detection and diagnosis T Wang, Z Liu, G Lu, J Liu IEEE Transactions on Industrial Electronics 68 (3), 2598-2607, 2020 | 61 | 2020 |
| Multiple-order graphical deep extreme learning machine for unsupervised fault diagnosis of rolling bearing X Zhao, M Jia, J Bin, T Wang, Z Liu IEEE Transactions on Instrumentation and Measurement 70, 1-12, 2020 | 52 | 2020 |
| Graph-based change detection for condition monitoring of rotating machines: Techniques for graph similarity T Wang, G Lu, J Liu, P Yan IEEE Transactions on Reliability 68 (3), 1034-1049, 2018 | 44 | 2018 |
| Multi-sensors based condition monitoring of rotary machines: An approach of multidimensional time-series analysis T Wang, G Lu, P Yan Measurement 134, 326-335, 2019 | 37 | 2019 |
| A probabilistic framework for remaining useful life prediction of bearings T Wang, Z Liu, N Mrad IEEE Transactions on Instrumentation and Measurement 70, 1-12, 2020 | 35 | 2020 |
| An adaptive deep learning framework for shipping container code localization and recognition R Zhang, Z Bahrami, T Wang, Z Liu IEEE Transactions on Instrumentation and Measurement 70, 1-13, 2020 | 24 | 2020 |
| Probabilistic analysis for remaining useful life prediction and reliability assessment T Wang, Z Liu, M Liao, N Mrad, G Lu IEEE Transactions on Reliability 71 (3), 1207-1218, 2020 | 14 | 2020 |
| Adaptive change detection for long-term machinery monitoring using incremental sliding-window T Wang, GL Lu, J Liu, P Yan Chinese Journal of Mechanical Engineering 30, 1338-1346, 2017 | 12 | 2017 |
| Life prediction for aircraft structure based on Bayesian inference: towards a digital twin ecosystem T Wang, Z Liu, M Liao, N Mrad Annual Conference of the PHM Society 12 (1), 8-8, 2020 | 10 | 2020 |
| Data modeling techniques for pipeline integrity assessment: A State-of-the-Art Survey J Ling, K Feng, T Wang, M Liao, C Yang, Z Liu IEEE Transactions on Instrumentation and Measurement, 2023 | 9 | 2023 |
| Probabilistic method for fatigue crack growth prediction with hybrid prior T Wang, J Bin, G Renaud, M Liao, G Lu, Z Liu International Journal of Fatigue 157, 106686, 2022 | 9 | 2022 |
| Digital twin and its application for the maintenance of aircraft T Wang, Z Liu Handbook of nondestructive evaluation 4.0, 1-19, 2021 | 9 | 2021 |
| Optimized deep neural network architectures with anchor box optimization for shipping container corrosion inspection Z Bahrami, R Zhang, R Rayhana, T Wang, Z Liu 2020 IEEE Symposium Series on Computational Intelligence (SSCI), 1328-1333, 2020 | 9 | 2020 |
| An end-to-end framework for shipping container corrosion defect inspection Z Bahrami, R Zhang, T Wang, Z Liu IEEE Transactions on Instrumentation and Measurement 71, 1-14, 2022 | 8 | 2022 |
| Digital Twin and Its Application for the Maintenance of Aircraft T Wang, Z Liu Handbook of Nondestructive Evaluation 4.0, 1035-1052, 2022 | 5 | 2022 |
| A probabilistic model for fatigue crack growth prediction based on closed-form solution T Wang, Z Bahrami, G Renaud, C Yang, M Liao, Z Liu Structures 44, 1583-1596, 2022 | 4 | 2022 |
| Unsupervised fault diagnosis of machine via multiple-order graphical deep extreme learning machine X Zhao, Z Liu, T Wang, J Bin, M Jia 2020 Asia-Pacific International Symposium on Advanced Reliability and …, 2020 | 4 | 2020 |
| Environment prediction to enhance the navigation system of water pipeline inspection platforms R Rayhana, Z Bahrami, T Wang, Z Liu, A Wu, X Kong 2021 IEEE 30th International Symposium on Industrial Electronics (ISIE), 1-6, 2021 | 3 | 2021 |
| Fault detection and diagnosis for PZT sensors with electro-mechanical impedance technique by using one-dimensional convolutional autoencoder M Kang, T Wang, S Pant, M Genest, Z Liu Health Monitoring of Structural and Biological Systems XV 11593, 20-31, 2021 | 3 | 2021 |
Zheng LiuUniversity of British Columbia (Okanagan)在 ubc.ca 的电子邮件经过验证
