HIGH VOLTAGE INSULATOR REAL-TIME CONDITION CLASSIFICATION

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dc.contributor.authorGylymbekov, Askar
dc.date.accessioned2024-06-22T17:53:21Z
dc.date.available2024-06-22T17:53:21Z
dc.date.issued2024-04-19
dc.description.abstractInsulators have a dual purpose of mechanically supporting and electrically isolating live phase conductors from the support tower in power systems. Due to experiencing harsh weather conditions, insulators may become contami nated or damaged. As a result, electrical and mechanical properties of insulator may deteri orate. Thus, it is significant to automize the process of condition classification of High Volt age insulator to prevent accidents and there fore ensuring secure service of transmission lines. This paper examines the effect of pol lution at insulator’s surfaces to the Dielectric Dissipation Factor and therefore research was conducted in 2 different disciplines: 1) Calculation of dielectric dissipation factor using Ansys Maxwell software; 2) High voltage in sulators contamination type classification us ing Convolutional Neural Networks. Ansys Maxwell software is used to simulate the Di electric Dissipation Factor of insulator under different types of contamination. In this part, three contamination levels (light, medium and heavy) will be considered which include soil, cement, iron, calcium and aluminum as pollu tants. The results show trend in which DDF increases with an increase of contamination level. In image classification part, Convolu tional Neural Networks will be used to cre ate a classifier. Insulators will be classified be tween 4 types and these are: clean, contami nated with soil, contaminated with water and contaminated with snow. Validation set assess ment results in 91% of accuracy.en_US
dc.identifier.citationGylymbekov, A. (2024). High Voltage Insulator Real-time Condition Classification. Nazarbayev University School of Engineering and Digital Sciencesen_US
dc.identifier.urihttp://nur.nu.edu.kz/handle/123456789/7949
dc.language.isoenen_US
dc.publisherNazarbayev University School of Engineering and Digital Sciencesen_US
dc.rightsAttribution-NonCommercial-NoDerivs 3.0 United States*
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/3.0/us/*
dc.subjectType of access: Open accessen_US
dc.subjectInsulatorsen_US
dc.subjectDielectric Dissipation Factoren_US
dc.subjectAnsysen_US
dc.subjectMachine Learningen_US
dc.subjectConvolutional Neural Networksen_US
dc.titleHIGH VOLTAGE INSULATOR REAL-TIME CONDITION CLASSIFICATIONen_US
dc.typeCapstone Projecten_US
workflow.import.sourcescience

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