Fault diagnosis of power electronic converter

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

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