| 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 | 159 | 2023 |
| 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 | 159 | 2022 |
| 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 | 134 | 2023 |
| Optimal demodulation-band selection for envelope-based diagnostics: A comparative study of traditional and novel tools WA Smith, P Borghesani, Q Ni, K Wang, Z Peng Mechanical Systems and Signal Processing 134, 106303, 2019 | 117 | 2019 |
| 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, 2023 | 90 | 2023 |
| Composite multi-scale weighted permutation entropy and extreme learning machine based intelligent fault diagnosis for rolling bearing J Zheng, Z Dong, H Pan, Q Ni, T Liu, J Zhang Measurement 143, 69-80, 2019 | 83 | 2019 |
| 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 | 73 | 2023 |
| 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 | 67 | 2017 |
| 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 | 60 | 2021 |
| 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 | 58 | 2023 |
| 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, 2023 | 57 | 2023 |
| 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 | 53 | 2017 |
| 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 | 48 | 2023 |
| Traversal index enhanced-gram (TIEgram): A novel optimal demodulation frequency band selection method for rolling bearing fault diagnosis under non-stationary operating conditions X Wang, J Zheng, Q Ni, H Pan, J Zhang Mechanical Systems and Signal Processing 172, 109017, 2022 | 48 | 2022 |
| 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 | 43 | 2023 |
| A novel order spectrum-based Vold-Kalman filter bandwidth selection scheme for fault diagnosis of gearbox in offshore wind turbines K Feng, JC Ji, K Wang, D Wei, C Zhou, Q Ni Ocean Engineering 266, 112920, 2022 | 41 | 2022 |
| A novel adaptive bandwidth selection method for Vold–Kalman filtering and its application in wind turbine planetary gearbox diagnostics K Feng, JC Ji, Q Ni Structural Health Monitoring 22 (2), 1027-1048, 2023 | 39 | 2023 |
| Spectral envelope-based adaptive empirical Fourier decomposition method and its application to rolling bearing fault diagnosis J Zheng, S Cao, H Pan, Q Ni ISA transactions 129, 476-492, 2022 | 38 | 2022 |
| A case study of sample entropy analysis to the fault detection of bearing in wind turbine Q Ni, K Feng, K Wang, B Yang, Y Wang Case studies in engineering failure analysis 9, 99-111, 2017 | 38 | 2017 |
| A novel similarity-based status characterization methodology for gear surface wear propagation monitoring K Feng, Q Ni, M Beer, H Du, C Li Tribology International 174, 107765, 2022 | 37 | 2022 |
Ke FengProfessor, Marie Curie Fellow, Xi'an Jiaotong UniversityBestätigte E-Mail-Adresse bei xjtu.edu.cn
