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Ke Feng
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Year
A fault information-guided variational mode decomposition (FIVMD) method for rolling element bearings diagnosis
Q Ni, JC Ji, K Feng, B Halkon
Mechanical Systems and Signal Processing 164, 108216, 2022
1592022
A review of vibration-based gear wear monitoring and prediction techniques
K Feng, JC Ji, Q Ni, M Beer
Mechanical Systems and Signal Processing 182, 109605, 2023
1572023
Digital twin-driven intelligent assessment of gear surface degradation
K Feng, JC Ji, Y Zhang, Q Ni, Z Liu, M Beer
Mechanical Systems and Signal Processing 186, 109896, 2023
1302023
Vibration-based updating of wear prediction for spur gears
K Feng, P Borghesani, WA Smith, RB Randall, ZY Chin, J Ren, Z Peng
Wear 426, 1410-1415, 2019
1252019
A fault diagnosis method for planetary gearboxes under non-stationary working conditions using improved Vold-Kalman filter and multi-scale sample entropy
Y Li, K Feng, X Liang, MJ Zuo
Journal of Sound and Vibration 439, 271-286, 2019
1122019
Physics-Informed LSTM hyperparameters selection for gearbox fault detection
Y Chen, M Rao, K Feng, MJ Zuo
Mechanical Systems and Signal Processing 171, 108907, 2022
922022
Use of cyclostationary properties of vibration signals to identify gear wear mechanisms and track wear evolution
K Feng, WA Smith, P Borghesani, RB Randall, Z Peng
Mechanical Systems and Signal Processing 150, 107258, 2021
922021
Data-driven prognostic scheme for bearings based on a novel health indicator and gated recurrent unit network
Q Ni, JC Ji, K Feng
IEEE Transactions on Industrial Informatics 19 (2), 1301-1311, 2022
882022
Vibration-based monitoring and prediction of surface profile change and pitting density in a spur gear wear process
K Feng, WA Smith, RB Randall, H Wu, Z Peng
Mechanical Systems and Signal Processing 165, 108319, 2022
752022
Digital twin-driven partial domain adaptation network for intelligent fault diagnosis of rolling bearing
Y Zhang, JC Ji, Z Ren, Q Ni, F Gu, K Feng, K Yu, J Ge, Z Lei, Z Liu
Reliability Engineering & System Safety 234, 109186, 2023
692023
A phase angle based diagnostic scheme to planetary gear faults diagnostics under non-stationary operational conditions
K Feng, K Wang, Q Ni, MJ Zuo, D Wei
Journal of Sound and Vibration 408, 190-209, 2017
672017
A novel correntropy-based band selection method for the fault diagnosis of bearings under fault-irrelevant impulsive and cyclostationary interferences
Q Ni, JC Ji, K Feng, B Halkon
Mechanical Systems and Signal Processing 153, 107498, 2021
592021
CFCNN: A novel convolutional fusion framework for collaborative fault identification of rotating machinery
Y Xu, K Feng, X Yan, R Yan, Q Ni, B Sun, Z Lei, Y Zhang, Z Liu
Information Fusion, 2023
582023
A novel vibration-based prognostic scheme for gear health management in surface wear progression of the intelligent manufacturing system
K Feng, JC Ji, Q Ni, Y Li, W Mao, L Liu
Wear, 204697, 2023
542023
An enhanced morphology gradient product filter for bearing fault detection
Y Li, MJ Zuo, Y Chen, K Feng
Mechanical Systems and Signal Processing 109, 166-184, 2018
542018
Supervised contrastive learning-based domain adaptation network for intelligent unsupervised fault diagnosis of rolling bearing
Y Zhang, Z Ren, S Zhou, K Feng, K Yu, Z Liu
IEEE/ASME Transactions on Mechatronics 27 (6), 5371-5380, 2022
532022
A diagnostic signal selection scheme for planetary gearbox vibration monitoring under non-stationary operational conditions
K Feng, KS Wang, M Zhang, Q Ni, MJ Zuo
Measurement Science and Technology 28 (3), 035003, 2017
532017
Physics-Informed Residual Network (PIResNet) for rolling element bearing fault diagnostics
Q Ni, JC Ji, B Halkon, K Feng, AK Nandi
Mechanical Systems and Signal Processing 200, 110544, 2023
432023
A novel gear fatigue monitoring indicator and its application to remaining useful life prediction for spur gear in intelligent manufacturing systems
K Feng, JC Ji, Q Ni
International Journal of Fatigue 168, 107459, 2023
422023
Attention-based multiscale denoising residual convolutional neural networks for fault diagnosis of rotating machinery
Y Xu, X Yan, K Feng, X Sheng, B Sun, Z Liu
Reliability Engineering & System Safety 226, 108714, 2022
412022
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