Incipient fault detection and diagnosis based on Kullback–Leibler divergence using principal component analysis: Part I J Harmouche, C Delpha, D Diallo Signal processing 94, 278-287, 2014 | 219 | 2014 |
Improved fault diagnosis of ball bearings based on the global spectrum of vibration signals J Harmouche, C Delpha, D Diallo IEEE Transactions on Energy Conversion 30 (1), 376-383, 2014 | 140 | 2014 |
The sliding singular spectrum analysis: A data-driven nonstationary signal decomposition tool J Harmouche, D Fourer, F Auger, P Borgnat, P Flandrin IEEE Transactions on Signal Processing 66 (1), 251-263, 2017 | 137 | 2017 |
Incipient fault detection and diagnosis based on Kullback–Leibler divergence using principal component analysis: Part II J Harmouche, C Delpha, D Diallo Signal Processing 109, 334-344, 2015 | 119 | 2015 |
Statistical approach for nondestructive incipient crack detection and characterization using Kullback-Leibler divergence J Harmouche, C Delpha, D Diallo, Y Le Bihan IEEE Transactions on Reliability 65 (3), 1360-1368, 2016 | 47 | 2016 |
Incipient fault amplitude estimation using KL divergence with a probabilistic approach J Harmouche, C Delpha, D Diallo Signal Processing 120, 1-7, 2016 | 45 | 2016 |
Leak detection in water distribution pipes using singular spectrum analysis R Cody, J Harmouche, S Narasimhan Urban Water Journal 15 (7), 636-644, 2018 | 42 | 2018 |
The ASTRES toolbox for mode extraction of non-stationary multicomponent signals D Fourer, J Harmouche, J Schmitt, T Oberlin, S Meignen, F Auger, ... 2017 25th European Signal Processing Conference (EUSIPCO), 1130-1134, 2017 | 39 | 2017 |
Long-term monitoring for leaks in water distribution networks using association rules mining J Harmouche, S Narasimhan IEEE Transactions on Industrial Informatics 16 (1), 258-266, 2019 | 30 | 2019 |
Mean shift clustering-based analysis of nonstationary vibration signals for machinery diagnostics S Fong, J Harmouche, S Narasimhan, J Antoni IEEE Transactions on Instrumentation and Measurement 69 (7), 4056-4066, 2019 | 25 | 2019 |
Faults diagnosis and detection using principal component analysis and Kullback-Leibler divergence J Harmouche, C Delpha, D Diallo IECON 2012-38th Annual Conference on IEEE Industrial Electronics Society …, 2012 | 20 | 2012 |
A global approach for the classification of bearing faults conditions using spectral features J Harmouche, C Delpha, D Diallo IECON 2013-39th Annual Conference of the IEEE Industrial Electronics Society …, 2013 | 19 | 2013 |
Linear discriminant analysis for the discrimination of faults in bearing balls by using spectral features J Harmouche, C Delpha, D Diallo 2014 First International Conference on Green Energy ICGE 2014, 182-187, 2014 | 15 | 2014 |
Statistical Incipient Fault Detection and Diagnosis with Kullback-Leibler Divergence: From Theory to Applications J Harmouche Supélec, 2014 | 11 | 2014 |
A theoretical approach for incipient fault severity assessment using the Kullback-Leibler Divergence J Harmouche, C Delpha, D Diallo 21st European Signal Processing Conference (EUSIPCO 2013), 1-5, 2013 | 11 | 2013 |
Capability evaluation of incipient fault detection in noisy environment: A theoretical Kullback-Leibler divergence-based approach for diagnosis A Youssef, J Harmouche, C Delpha, D Diallo IECON 2013-39th Annual Conference of the IEEE Industrial Electronics Society …, 2013 | 8 | 2013 |
Une ou deux composantes: la réponse de l’analyse spectrale singulière J Harmouche, D Fourer, F Auger, P Borgnat, P Flandrin Actes du colloque GRETSI, 2015 | 5 | 2015 |
One or two components? the singular spectrum analysis answers J Harmouche, D Fourer, P Flandrin, F Auger, P Borgnat Reconstruction 1, 1, 2015 | 5 | 2015 |
Bearing fault diagnosis in rotating machines C Delpha, D Diallo, J Harmouche, M Benbouzid, Y Amirat, E Elbouchikhi Electrical systems 2: From diagnosis to prognosis, 123-151, 2020 | 4 | 2020 |
Discrimination des défauts de roulements par une analyse spectrale globale J Harmouche, D Diallo, C Delpha Symposium de Génie Électrique 2014, 2014 | 3 | 2014 |