| A perspective survey on deep transfer learning for fault diagnosis in industrial scenarios: Theories, applications and challenges W Li, R Huang, J Li, Y Liao, Z Chen, G He, R Yan, K Gryllias Mechanical Systems and Signal Processing 167, 108487, 2022 | 440 | 2022 |
| A deep learning method for bearing fault diagnosis based on cyclic spectral coherence and convolutional neural networks Z Chen, A Mauricio, W Li, K Gryllias Mechanical Systems and Signal Processing 140, 106683, 2020 | 349 | 2020 |
| Mechanical fault diagnosis using Convolutional Neural Networks and Extreme Learning Machine Z Chen, K Gryllias, W Li Mechanical Systems and Signal Processing 133, 2019 | 296 | 2019 |
| Rolling element bearing fault detection in industrial environments based on a K-means clustering approach CT Yiakopoulos, KC Gryllias, IA Antoniadis Expert Systems with Applications 38 (3), 2888-2911, 2011 | 286 | 2011 |
| A Support Vector Machine approach based on physical model training for rolling element bearing fault detection in industrial environments KC Gryllias, IA Antoniadis Engineering Applications of Artificial Intelligence 25 (2), 326-344, 2012 | 260 | 2012 |
| Intelligent fault diagnosis for rotary machinery using transferable convolutional neural network Z Chen, K Gryllias, W Li IEEE Transactions on Industrial Informatics 16 (1), 339-349, 2019 | 250 | 2019 |
| Domain adversarial transfer network for cross-domain fault diagnosis of rotary machinery Z Chen, G He, J Li, Y Liao, K Gryllias, W Li IEEE Transactions on Instrumentation and Measurement 69 (11), 8702-8712, 2020 | 209 | 2020 |
| KDamping: A stiffness based vibration absorption concept IA Antoniadis, SA Kanarachos, K Gryllias, IE Sapountzakis Journal of Vibration and Control 24 (3), 588-606, 2018 | 137 | 2018 |
| A semi-supervised Support Vector Data Description-based fault detection method for rolling element bearings based on cyclic spectral analysis C Liu, K Gryllias Mechanical Systems and Signal Processing 140, 106682, 2020 | 102 | 2020 |
| Improved Envelope Spectrum via Feature Optimisation-gram (IESFOgram): A novel tool for rolling element bearing diagnostics under non-stationary operating conditions A Mauricio, WA Smith, RB Randall, J Antoni, K Gryllias Mechanical Systems and Signal Processing 144, 106891, 2020 | 100 | 2020 |
| Estimation of the instantaneous rotation speed using complex shifted Morlet wavelets KC Gryllias, IA Antoniadis Mechanical Systems and Signal Processing 38 (1), 78-95, 2013 | 73 | 2013 |
| Bearing diagnostics under strong electromagnetic interference based on Integrated Spectral Coherence A Mauricio, J Qi, WA Smith, M Sarazin, RB Randall, K Janssens, ... Mechanical systems and signal processing 140, 106673, 2020 | 65 | 2020 |
| Cyclostationary-based Multiband Envelope Spectra Extraction for bearing diagnostics: The Combined Improved Envelope Spectrum A Mauricio, K Gryllias Mechanical Systems and Signal Processing 149, 2021 | 64 | 2021 |
| Vibration based condition monitoring of wind turbine gearboxes based on cyclostationary analysis A Mauricio, J Qi, K Gryllias ASME 2018 Turbo Expo - Turbomachinery Technical Conference & Exposition …, 2018 | 57* | 2018 |
| Simulation-driven domain adaptation for rolling element bearing fault diagnosis C Liu, K Gryllias IEEE Transactions on Industrial Informatics 18 (9), 5760-5770, 2021 | 55 | 2021 |
| A general anomaly detection framework for fleet-based condition monitoring of machines K Hendrickx, W Meert, Y Mollet, J Gyselinck, B Cornelis, K Gryllias, ... Mechanical Systems and Signal Processing 139, 106585, 2020 | 55 | 2020 |
| A discrepancy analysis methodology for rolling element bearing diagnostics under variable speed conditions S Schmidt, PS Heyns, KC Gryllias Mechanical Systems and Signal Processing 116, 40-61, 2019 | 50 | 2019 |
| Cyclostationary modeling for local fault diagnosis of planetary gear vibration signals RB Sun, ZB Yang, K Gryllias, XF Chen Journal of Sound and Vibration 471, 115175, 2020 | 48 | 2020 |
| An informative frequency band identification framework for gearbox fault diagnosis under time-varying operating conditions S Schmidt, PS Heyns, KC Gryllias Mechanical Systems and Signal Processing 158, 107771, 2021 | 40 | 2021 |
| A peak energy criterion (pe) for the selection of resonance bands in complex shifted morlet wavelet (csmw) based demodulation of defective rolling element bearings vibration … KC Gryllias, I Antoniadis International Journal of Wavelets, Multiresolution and Information …, 2009 | 38 | 2009 |
Alexandre MauricioPhD student, KU Leuven在 kuleuven.be 的电子邮件经过验证
