An improved PCA scheme for sensor FDI: Application to an air quality monitoring network MF Harkat, G Mourot, J Ragot Journal of Process Control 16 (6), 625-634, 2006 | 178 | 2006 |
Hidden Markov model based principal component analysis for intelligent fault diagnosis of wind energy converter systems A Kouadri, M Hajji, MF Harkat, K Abodayeh, M Mansouri, H Nounou, ... Renewable Energy 150, 598-606, 2020 | 157 | 2020 |
Online reduced kernel principal component analysis for process monitoring R Fezai, M Mansouri, O Taouali, MF Harkat, N Bouguila Journal of Process Control 61, 1-11, 2018 | 118 | 2018 |
Multivariate feature extraction based supervised machine learning for fault detection and diagnosis in photovoltaic systems M Hajji, MF Harkat, A Kouadri, K Abodayeh, M Mansouri, H Nounou, ... European Journal of Control 59, 313-321, 2021 | 109 | 2021 |
Moving window KPCA with reduced complexity for nonlinear dynamic process monitoring I Jaffel, O Taouali, MF Harkat, H Messaoud ISA transactions 64, 184-192, 2016 | 88 | 2016 |
Shading fault detection in a grid-connected PV system using vertices principal component analysis L Rouani, MF Harkat, A Kouadri, S Mekhilef Renewable Energy 164, 1527-1539, 2021 | 71 | 2021 |
Wavelet optimized EWMA for fault detection and application to photovoltaic systems MN Majdi Mansouri, Ayman Al-khazraji, Mansour Hajji, Mohamed Faouzi Harkat ... Solar Energy 167, 125-136, 2018 | 71 | 2018 |
New fault detection method based on reduced kernel principal component analysis (RKPCA) O Taouali, I Jaffel, H Lahdhiri, MF Harkat, H Messaoud The International Journal of Advanced Manufacturing Technology 85, 1547-1552, 2016 | 70 | 2016 |
New reduced kernel PCA for fault detection and diagnosis in cement rotary kiln F Bencheikh, MF Harkat, A Kouadri, A Bensmail Chemometrics and Intelligent Laboratory Systems 204, 104091, 2020 | 65 | 2020 |
Data-driven and model-based methods for fault detection and diagnosis M Mansouri, MF Harkat, HN Nounou, MN Nounou Elsevier, 2020 | 64 | 2020 |
Fault detection of uncertain chemical processes using interval partial least squares-based generalized likelihood ratio test MF Harkat, M Mansouri, MN Nounou, HN Nounou Information Sciences 490, 265-284, 2019 | 63 | 2019 |
An effective statistical fault detection technique for grid connected photovoltaic systems based on an improved generalized likelihood ratio test M Mansouri, M Hajji, M Trabelsi, MF Harkat, A Al-khazraji, A Livera, ... Energy 159, 842-856, 2018 | 63 | 2018 |
Sensor fault detection, isolation and reconstruction using nonlinear principal component analysis MF Harkat, S Djelel, N Doghmane, M Benouaret International Journal of Automation and Computing 4, 149-155, 2007 | 63 | 2007 |
On the application of interval PCA to process monitoring: A robust strategy for sensor FDI with new efficient control statistics T Ait-Izem, MF Harkat, M Djeghaba, F Kratz Journal of Process Control 63, 29-46, 2018 | 62 | 2018 |
Fault detection of uncertain nonlinear process using interval-valued data-driven approach MF Harkat, M Mansouri, M Nounou, H Nounou Chemical Engineering Science 205, 36-45, 2019 | 56 | 2019 |
A new fault detection method for nonlinear process monitoring R Fazai, O Taouali, MF Harkat, N Bouguila The International Journal of Advanced Manufacturing Technology 87, 3425-3436, 2016 | 54 | 2016 |
Détection et localisation de défauts par analyse en composantes principales MF Harkat Institut National Polytechnique de Lorraine-INPL, 2003 | 54 | 2003 |
Kernel principal component analysis with reduced complexity for nonlinear dynamic process monitoring I Jaffel, O Taouali, MF Harkat, H Messaoud The International Journal of Advanced Manufacturing Technology 88, 3265-3279, 2017 | 48 | 2017 |
Enhanced data validation strategy of air quality monitoring network MF Harkat, M Mansouri, M Nounou, H Nounou Environmental research 160, 183-194, 2018 | 45 | 2018 |
Supervised process monitoring and fault diagnosis based on machine learning methods H Lahdhiri, M Said, KB Abdellafou, O Taouali, MF Harkat The International Journal of Advanced Manufacturing Technology 102, 2321-2337, 2019 | 41 | 2019 |