| Experimental setup for online fault diagnosis of induction machines via promising IoT and machine learning: Towards industry 4.0 empowerment MQ Tran, M Elsisi, K Mahmoud, MK Liu, M Lehtonen, MMF Darwish IEEE access 9, 115429-115441, 2021 | 108 | 2021 |
| Milling chatter detection using scalogram and deep convolutional neural network MQ Tran, MK Liu, QV Tran The International Journal of Advanced Manufacturing Technology 107 (3), 1505 …, 2020 | 90 | 2020 |
| Effective multi-sensor data fusion for chatter detection in milling process MQ Tran, MK Liu, M Elsisi ISA transactions 125, 514-527, 2022 | 84 | 2022 |
| Reliable deep learning and IoT-based monitoring system for secure computer numerical control machines against cyber-attacks with experimental verification MQ Tran, M Elsisi, MK Liu, VQ Vu, K Mahmoud, MMF Darwish, ... IEEE Access 10, 23186-23197, 2022 | 76 | 2022 |
| Effective fault diagnosis based on wavelet and convolutional attention neural network for induction motors MQ Tran, MK Liu, QV Tran, TK Nguyen IEEE Transactions on Instrumentation and Measurement 71, 1-13, 2021 | 75 | 2021 |
| Effective feature selection with fuzzy entropy and similarity classifier for chatter vibration diagnosis MQ Tran, M Elsisi, MK Liu Measurement 184, 109962, 2021 | 71 | 2021 |
| Tool wear monitoring and prediction based on sound signal MK Liu, YH Tseng, MQ Tran The International Journal of Advanced Manufacturing Technology 103, 3361-3373, 2019 | 67 | 2019 |
| Robust fault recognition and correction scheme for induction motors using an effective IoT with deep learning approach MQ Tran, M Amer, AY Abdelaziz, HJ Dai, MK Liu, M Elsisi Measurement 207, 112398, 2023 | 47 | 2023 |
| Hand gesture recognition by a MMG-based wearable device MK Liu, YT Lin, ZW Qiu, CK Kuo, CK Wu IEEE Sensors Journal 20 (24), 14703-14712, 2020 | 30 | 2020 |
| Data science for vibration heteroscedasticity and predictive maintenance of rotary bearings CY Lee, TS Huang, MK Liu, CY Lan Energies 12 (5), 801, 2019 | 30 | 2019 |
| Fusion of vibration and current signatures for the fault diagnosis of induction machines MK Liu, MQ Tran, PY Weng Shock and Vibration 2019, 2019 | 29 | 2019 |
| Simultaneous time–frequency control of bifurcation and chaos MK Liu, CS Suh Communications in Nonlinear Science and Numerical Simulation 17 (6), 2539-2550, 2012 | 29 | 2012 |
| Control of cutting vibration and machining instability: a time-frequency approach for precision, micro and nano machining CS Suh, MK Liu John Wiley & Sons, 2013 | 26 | 2013 |
| Hybrid model-and signal-based chatter detection in the milling process MK Liu, MQ Tran, C Chung, YW Qui Journal of Mechanical Science and Technology 34, 1-10, 2020 | 24 | 2020 |
| Multi-dimensional time-frequency control of micro-milling instability MK Liu, EB Halfmann, CS Suh Journal of Vibration and Control 20 (5), 643-660, 2014 | 21 | 2014 |
| Induction motor faults diagnosis using support vector machine to the motor current signature H Guo, MK Liu 2018 IEEE Industrial Cyber-Physical Systems (ICPS), 417-421, 2018 | 20 | 2018 |
| On controlling milling instability and chatter at high speed MK Liu, CS Suh Journal of Applied Nonlinear Dynamics 1 (1), 59-72, 2012 | 19 | 2012 |
| Temporal and spectral responses of a softening Duffing oscillator undergoing route-to-chaos MK Liu, CS Suh Communications in Nonlinear Science and Numerical Simulation 17 (12), 5217-5228, 2012 | 14 | 2012 |
| Estimation of process damping coefficient using dynamic cutting force model C Chung, MQ Tran, MK Liu International Journal of Precision Engineering and Manufacturing 21, 623-632, 2020 | 13 | 2020 |
| Fault diagnosis of ball bearing elements: A generic procedure based on time-frequency analysis MK Liu, PY Weng Measurement Science Review 19 (4), 185-194, 2019 | 13 | 2019 |
Minh-Quang TranNational Taiwan University of Science and Technology在 mail.ntust.edu.tw 的电子邮件经过验证
