Please use this identifier to cite or link to this item:
https://dspace.univ-ouargla.dz/jspui/handle/123456789/37123
Title: | Fault diagnosis of power electronic converter |
Authors: | ROUABAH, Boubakeur AD, Hana SERKOU, Arwa Oum elbaha |
Keywords: | Modular Multilevel Converter Machine learning power conversion systems |
Issue Date: | 2024 |
Publisher: | UNIVERSITY OF KASDI MERBAH OUARGLA |
Citation: | FACULTY OF NEW TECHNOLOGIES OF INFORMATION AND COMMUNICATION |
Abstract: | Modular Multilevel Converter MMCs are an advanced power electronics topology that has many advantages, including high efficiency, scalability, and superior harmonic performance. However, as with any complex system, MMC devices are susceptible ti errors that can affect their operation and reliability. Machine learning is one of the most important technologies to enhance fault diagnosis in MMC, enabling rapid identification and remediation of problems to reliability of power conversion systems. |
Description: | Instrumentation and System |
URI: | https://dspace.univ-ouargla.dz/jspui/handle/123456789/37123 |
Appears in Collections: | Département d'Electronique et des Télécommunications - Master |
Files in This Item:
File | Description | Size | Format | |
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AD-SERKOU.pdf | Instrumentation and System | 2,38 MB | Adobe PDF | View/Open |
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