Eine Plattform für die Wissenschaft: Bauingenieurwesen, Architektur und Urbanistik
Eine Plattform für die Wissenschaft: Bauingenieurwesen, Architektur und Urbanistik
Inspection of High Voltage Insulators with a Deep Learning Model
Electric utility firms must be consistent since they are subjected to distinct routine assessments. Lines with inadequate connections might cause large power outages or blackouts if not adequately inspected. As a result, numerous studies have been conducted to inspect elements such as high voltage insulators, electric poles, and twisted conductors. This paper describes a vision-based approach for monitoring the health of ceramic insulators that uses a camera picture as its source and a deep structured learning model for autonomous data interpretation. Every image patch has been classified using a deep learning model. The current work was carried out using data containing 2000 insulator pictures (size of 256 x 256). The suggested system is unique in that it is integrated with the Internet of Things and an embedded device via the Deep Learning Platform. For this study, a sample of image was supplied to the Raspberry Pi in order to determine the health of an insulator. The experimental results reveal that the suggested approach is fast and accurate at detecting and classifying insulators.
Inspection of High Voltage Insulators with a Deep Learning Model
Electric utility firms must be consistent since they are subjected to distinct routine assessments. Lines with inadequate connections might cause large power outages or blackouts if not adequately inspected. As a result, numerous studies have been conducted to inspect elements such as high voltage insulators, electric poles, and twisted conductors. This paper describes a vision-based approach for monitoring the health of ceramic insulators that uses a camera picture as its source and a deep structured learning model for autonomous data interpretation. Every image patch has been classified using a deep learning model. The current work was carried out using data containing 2000 insulator pictures (size of 256 x 256). The suggested system is unique in that it is integrated with the Internet of Things and an embedded device via the Deep Learning Platform. For this study, a sample of image was supplied to the Raspberry Pi in order to determine the health of an insulator. The experimental results reveal that the suggested approach is fast and accurate at detecting and classifying insulators.
Inspection of High Voltage Insulators with a Deep Learning Model
J. Inst. Eng. India Ser. B
Sarkar, Dipu (Autor:in) / Gunturi, Sravan Kumar (Autor:in)
Journal of The Institution of Engineers (India): Series B ; 103 ; 1229-1238
01.08.2022
10 pages
Aufsatz (Zeitschrift)
Elektronische Ressource
Englisch
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