Zobrazeno 1 - 10
of 19
pro vyhledávání: '"A. Nait Seghir"'
Autor:
Mohamed-Dhiaeddine Drid, Samir Hamdani, Amirouche Nait-Seghir, Larbi Chrifi-Alaoui, Sami Labdai, Said Drid
Publikováno v:
Applied Sciences, Vol 14, Iss 21, p 9782 (2024)
This paper addresses the challenge of integrating multiple energy sources into a single-domain microgrid, commonly found in urban buildings, while also providing a platform for energy management. A Lyapunov stability analysis of a simple boost conver
Externí odkaz:
https://doaj.org/article/01fdf63f83444058b8add5b811c15870
Autor:
Drid, Mohamed-Dhiaeddine, Hamdani, Samir, Nait-Seghir, Amirouche, Chrifi-Alaoui, Larbi, Labdai, Sami, Drid, Said
Publikováno v:
Applied Sciences (2076-3417); Nov2024, Vol. 14 Issue 21, p9782, 22p
Publikováno v:
2022 IEEE 21st international Ccnference on Sciences and Techniques of Automatic Control and Computer Engineering (STA).
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::6e9e77532fdbb4691be3cce115dbfb54
https://doi.org/10.1109/sta56120.2022.10019081
https://doi.org/10.1109/sta56120.2022.10019081
Multiple features extraction and selection for detection and classification of stator winding faults
Publikováno v:
IET Electric Power Applications. 12:339-346
In this study, a new effective approach for detection and classification of stator winding faults in induction motors is presented. The approach is based on current analysis. It uses multiple features extraction techniques, where Park transform, zero
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::cd2040faee9616c5a5fcd00ef7c5878a
https://doi.org/10.1049/iet-epa.2017.0457
https://doi.org/10.1049/iet-epa.2017.0457
Publikováno v:
International Journal of Digital Signals and Smart Systems. 5:63
This paper presents high performances fault detection and diagnosis approach for broken rotor bar (BRB) and severity evaluation in squirrel cage induction motors. The proposed approach is based on combination of multiple features extraction technique
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::c1724638e7ac7be51d2397dd5ef7cb46
https://doi.org/10.1504/ijdsss.2021.112795
https://doi.org/10.1504/ijdsss.2021.112795
Self-Organizing Map and feature selection for of IM broken rotor bars faults detection and diagnosis
Publikováno v:
2018 International Conference on Electrical Sciences and Technologies in Maghreb (CISTEM).
This paper presents a new robust and high performances fault diagnosis scheme for broken bar fault detection and severity evaluation. The aim is to ensure an accurate condition monitoring and reduced false or missed alarms rate for induction motor op
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::b706e9350e186d5832749fe13c89842e
https://doi.org/10.1109/cistem.2018.8613361
https://doi.org/10.1109/cistem.2018.8613361
Publikováno v:
Lecture Notes in Electrical Engineering ISBN: 9783319489285
Mechanical faults account for a large majority of the faults in the electrical rotating machinery, it can result in partial or total breakdown of a motor. Therefore, their diagnosis is an intensively investigated field of research. This paper investi
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::4b40c6ee8d44f8f0a816e96c08a62f88
https://doi.org/10.1007/978-3-319-48929-2_18
https://doi.org/10.1007/978-3-319-48929-2_18
Publikováno v:
2015 IEEE 10th International Symposium on Diagnostics for Electrical Machines, Power Electronics and Drives (SDEMPED).
Misalignment is one of the most common mechanical faults in electrical rotating machinery, it can lead to partial or total breakdown of a motor in the long run may. This paper investigates the application of the Autoregressive Model of torque signal
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::396ac6320acbdc9b160a5f9a2691862c
https://doi.org/10.1109/demped.2015.7303709
https://doi.org/10.1109/demped.2015.7303709
Publikováno v:
2015 3rd International Conference on Control, Engineering & Information Technology (CEIT).
Mechanical faults present a large portion of induction motor failures, if left undetected, it can lead to partial or total breakdown of the machine. This paper propose a scheme to detect and diagnose mechanical faults in an induction motor by the AR
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::88b996015082d861316a9ff3cce9c9e4
https://doi.org/10.1109/ceit.2015.7232984
https://doi.org/10.1109/ceit.2015.7232984
Publikováno v:
Recent Advances in Electrical Engineering & Control Applications; 2017, p233-246, 14p