Zobrazeno 1 - 10
of 50
pro vyhledávání: '"Abdelmalek Kouadri"'
Autor:
Mohammed Tahar Habib Kaib, Abdelmalek Kouadri, Mohamed-Faouzi Harkat, Abderazak Bensmail, Majdi Mansouri
Publikováno v:
IEEE Access, Vol 12, Pp 11470-11480 (2024)
Fault detection and diagnosis (FDD) systems play a crucial role in maintaining the adequate execution of the monitored process. One of the widely used data-driven FDD methods is the Principal Component Analysis (PCA). Unfortunately, PCA’s reliabili
Externí odkaz:
https://doaj.org/article/4de09f34ad044addab9eecd189d8572e
Autor:
Khadija Attouri, Majdi Mansouri, Mansour Hajji, Abdelmalek Kouadri, Kais Bouzrara, Hazem Nounou
Publikováno v:
Signals, Vol 4, Iss 2, Pp 381-400 (2023)
In this work, an effective Fault Detection and Diagnosis (FDD) strategy designed to increase the performance and accuracy of fault diagnosis in grid-connected photovoltaic (GCPV) systems is developed. The evolved approach is threefold: first, a pre-p
Externí odkaz:
https://doaj.org/article/6d949fa81a404717971f6c8f997ac780
Autor:
Radhia Fezai, Kamaleldin Abodayeh, Majdi Mansouri, Abdelmalek Kouadri, Mohamed-Faouzi Harkat, Hazem Nounou, Mohamed Nounou, Hassani Messaoud
Publikováno v:
IEEE Access, Vol 8, Pp 78343-78353 (2020)
Kernel partial least squares (KPLS) models are widely used as nonlinear data-driven methods for faults detection (FD) in industrial processes. However, KPLS models lead to irrelevant performance over long operation periods due to process parameters c
Externí odkaz:
https://doaj.org/article/caa9cd029c7f4c5184986f106d165c91
Autor:
Nounou, Khadija Attouri, Majdi Mansouri, Mansour Hajji, Abdelmalek Kouadri, Kais Bouzrara, Hazem
Publikováno v:
Signals; Volume 4; Issue 2; Pages: 381-400
In this work, an effective Fault Detection and Diagnosis (FDD) strategy designed to increase the performance and accuracy of fault diagnosis in grid-connected photovoltaic (GCPV) systems is developed. The evolved approach is threefold: first, a pre-p
Autor:
Khadija Attouri, Majdi Mansouri, Mansour Hajji, Abdelmalek Kouadri, Kais Bouzrara, Hazem Nounou
Publikováno v:
Sustainability
Volume 15
Issue 4
Pages: 3191
Volume 15
Issue 4
Pages: 3191
In this paper, we present a novel and effective fault detection and diagnosis (FDD) method for a wind energy converter (WEC) system with a nominal power of 15 KW, which is designed to significantly reduce the complexity and computation time and possi
Autor:
Hazem Nounou, Mansour Hajji, Majdi Mansouri, Abdelmalek Kouadri, Kamaleldin Abodayeh, Mohamed-Faouzi Harkat, Mohamed Nounou
Publikováno v:
European Journal of Control. 59:313-321
Fault detection and diagnosis (FDD) in the photovoltaic (PV) array has become a challenge due to the magnitudes of the faults, the presence of maximum power point trackers, non-linear PV characteristics, and the dependence on isolation efficiency. Th
Autor:
Abdelhalim Louifi, Salah Eddine Louhab, Abdelmalek Kouadri, Lahcene Rouani, Abderazak Bensmail, Mohamed Faouzi Harkat
Publikováno v:
2022 19th International Multi-Conference on Systems, Signals & Devices (SSD).
Publikováno v:
Renewable Energy. 164:1527-1539
Partial shading severely impacts the performance of the photovoltaic (PV) system by causing power losses and creating hotspots across the shaded cells or modules. Proper detection of shading faults serves not only in harvesting the desired power from
Autor:
Khaled Dhibi, Majdi Mansouri, Abdelmalek Kouadri, Mohamed Nounou, Kais Bouzara, Radhia Fezai, Mohamed Trabelsi, Hazem Nounou
Publikováno v:
IEEE Journal of Photovoltaics. 10:1864-1871
The random forest (RF) classifier, which is a combination of tree predictors, is one of the most powerful classification algorithms that has been recently applied for fault detection and diagnosis (FDD) of industrial processes. However, RF is still s
Autor:
Abdelmalek Kouadri, Majdi Mansouri, Kais Bouzara, Mohamed Nounou, Hazem Nounou, Khaled Dhibi, Radhia Fezai, Mohamed-Faouzi Harkat
Publikováno v:
IEEE Sensors Journal. 20:10228-10239
Kernel principal component analysis (KPCA) is a well-established data-driven process modeling and monitoring framework that has long been praised for its performances. However, it is still not optimal for large-scale and uncertain systems. Applying K