| Gearbox Tooth Cut Fault Diagnostics Using Acoustic Emission and Vibration Sensors—A Comparative Study Qu Y, He D, Yoon J, Van Hecke B, Bechhoefer E, Zhu Sensors 14 (1), 1372-1393, 2014 | 145 | 2014 |
| Lubrication Oil Condition Monitoring and Remaining Useful Life Prediction with Particle Filtering J Zhu, J Yoon, D He, Y Qu, E Bechhoefer International Journal of Prognostics and Health Management, 2013 | 138 | 2013 |
| Semi-supervised gear fault diagnosis using raw vibration signal based on deep learning LI Xueyi, LI Jialin, QU Yongzhi, HE David Chinese Journal of Aeronautics 33 (2), 418-426, 2020 | 97 | 2020 |
| Gear pitting fault diagnosis using integrated CNN and GRU network with both vibration and acoustic emission signals X Li, J Li, Y Qu, D He Applied Sciences 9 (4), 768, 2019 | 93 | 2019 |
| Gear pitting fault diagnosis with mixed operating conditions based on adaptive 1D separable convolution with residual connection X Li, J Li, C Zhao, Y Qu, D He Mechanical Systems and Signal Processing 142, 106740, 2020 | 78 | 2020 |
| Vibration response of multi-span fluid-conveying pipe with multiple accessories under complex boundary conditions M Liu, Z Wang, Z Zhou, Y Qu, Z Yu, Q Wei, L Lu European Journal of Mechanics-A/Solids 72, 41-56, 2018 | 68 | 2018 |
| A New Acousbc Emission Sensor Based Gear Fault Detection Approach Y Qu, E Bechhoefer, D He, J Zhu International Journal of Prognostics and Health Management 11, 1-14, 2013 | 67 | 2013 |
| Detection of pitting in gears using a deep sparse autoencoder Y Qu, M He, J Deutsch, D He Applied Sciences 7 (5), 515, 2017 | 63 | 2017 |
| A novel vibration-based fault diagnostic algorithm for gearboxes under speed fluctuations without rotational speed measurement L Hong, Y Qu, JS Dhupia, S Sheng, Y Tan, Z Zhou Mechanical Systems and Signal Processing 94, 14-32, 2017 | 53 | 2017 |
| Unsupervised rotating machinery fault diagnosis method based on integrated SAE–DBN and a binary processor J Li, X Li, D He, Y Qu Journal of Intelligent Manufacturing 31, 1899-1916, 2020 | 52 | 2020 |
| Bearing fault diagnosis based on a new acoustic emission sensor technique B Van Hecke, Y Qu, D He Proceedings of the Institution of Mechanical Engineers, Part O: Journal of …, 2015 | 49 | 2015 |
| A domain adaptation model for early gear pitting fault diagnosis based on deep transfer learning network J Li, X Li, D He, Y Qu Proceedings of the Institution of Mechanical Engineers, Part O: Journal of …, 2020 | 40 | 2020 |
| Signal processing techniques to improve an acoustic emissions sensor E Bechhoefer, Y Qu, J Zhu, D He Annual Conference of the PHM Society 5 (1), 2013 | 39 | 2013 |
| Clamp looseness detection using modal strain estimated from FBG based operational modal analysis Z Wang, M Liu, Z Zhu, Y Qu, Q Wei, Z Zhou, Y Tan, Z Yu, F Yang Measurement 137, 82-97, 2019 | 37 | 2019 |
| Deep and broad learning on content-aware POI recommendation F Wang, Y Qu, L Zheng, CT Lu, SY Philip 2017 IEEE 3rd International Conference on Collaboration and Internet …, 2017 | 34 | 2017 |
| Dynamic modeling of manufacturing capability for robotic disassembly in remanufacturing Z Zheng, W Xu, Z Zhou, DT Pham, Y Qu, J Zhou Procedia Manufacturing 10, 15-25, 2017 | 33 | 2017 |
| A novel method for early gear pitting fault diagnosis using stacked SAE and GBRBM J Li, X Li, D He, Y Qu Sensors 19 (4), 758, 2019 | 32 | 2019 |
| A Fiber Bragg Grating Sensing Based Triaxial Vibration Sensor MLZZ Tianliang Li, Yuegang Tan, Yi Liu, Yongzhi Qu Sensors 15 (9), 24214-24229, 2015 | 32 | 2015 |
| On the use of spectral averaging of acoustic emission signals for bearing fault diagnostics B Van Hecke, D He, Y Qu Journal of Vibration and Acoustics 136 (6), 061009, 2014 | 32 | 2014 |
| The detection of the pipe crack utilizing the operational modal strain identified from fiber Bragg grating Z Wang, M Liu, Y Qu, Q Wei, Z Zhou, Y Tan, L Hong, H Song Sensors 19 (11), 2556, 2019 | 29 | 2019 |
David HeDepartment of Mechanical and Industrial Engineering, The University of Illinois at Chicago在 uic.edu 的电子邮件经过验证
