Detection of overhead line glass insulator condition using dual function device and deep learning approach
This paper presents a design of a multifunction smart wireless device for online condition monitoring of transmission line insulators. The proposed device can measure the insulator leakage current and take images of the high-voltage insulation. Yolov5-based models and deep convolutional neural netwo...
| Published in: | Computers and Electrical Engineering |
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| Format: | Article |
| Language: | English |
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Elsevier Ltd
2024
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| Online Access: | https://www.scopus.com/inward/record.uri?eid=2-s2.0-85206828195&doi=10.1016%2fj.compeleceng.2024.109764&partnerID=40&md5=3eb98eff8e930097117f232a9088e162 |
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2-s2.0-85206828195 Salem A.A.A.; Lau K.Y.; Abu-Saida A. Detection of overhead line glass insulator condition using dual function device and deep learning approach 2024 Computers and Electrical Engineering 120 10.1016/j.compeleceng.2024.109764 https://www.scopus.com/inward/record.uri?eid=2-s2.0-85206828195&doi=10.1016%2fj.compeleceng.2024.109764&partnerID=40&md5=3eb98eff8e930097117f232a9088e162 This paper presents a design of a multifunction smart wireless device for online condition monitoring of transmission line insulators. The proposed device can measure the insulator leakage current and take images of the high-voltage insulation. Yolov5-based models and deep convolutional neural networks (DCCN) are developed to analyze and classify the measured data and estimate the insulator's health condition. We have developed and tested a prototype of the proposed device. The device can issue a real-time warning message when a sudden change takes place in the leakage current value. The control center or smartphones receive the collected data wirelessly. We analyze the transmitted data using the developed methods to detect any anomalies and take appropriate remedial action. The performance and feasibility of the developed device are assessed through extensive experimental analysis. Results attest to the robustness of the proposed device, which is easy to install for existing and future overhead transmission line insulators. © 2024 Elsevier Ltd Elsevier Ltd 00457906 English Article |
| author |
Salem A.A.A.; Lau K.Y.; Abu-Saida A. |
| spellingShingle |
Salem A.A.A.; Lau K.Y.; Abu-Saida A. Detection of overhead line glass insulator condition using dual function device and deep learning approach |
| author_facet |
Salem A.A.A.; Lau K.Y.; Abu-Saida A. |
| author_sort |
Salem A.A.A.; Lau K.Y.; Abu-Saida A. |
| title |
Detection of overhead line glass insulator condition using dual function device and deep learning approach |
| title_short |
Detection of overhead line glass insulator condition using dual function device and deep learning approach |
| title_full |
Detection of overhead line glass insulator condition using dual function device and deep learning approach |
| title_fullStr |
Detection of overhead line glass insulator condition using dual function device and deep learning approach |
| title_full_unstemmed |
Detection of overhead line glass insulator condition using dual function device and deep learning approach |
| title_sort |
Detection of overhead line glass insulator condition using dual function device and deep learning approach |
| publishDate |
2024 |
| container_title |
Computers and Electrical Engineering |
| container_volume |
120 |
| container_issue |
|
| doi_str_mv |
10.1016/j.compeleceng.2024.109764 |
| url |
https://www.scopus.com/inward/record.uri?eid=2-s2.0-85206828195&doi=10.1016%2fj.compeleceng.2024.109764&partnerID=40&md5=3eb98eff8e930097117f232a9088e162 |
| description |
This paper presents a design of a multifunction smart wireless device for online condition monitoring of transmission line insulators. The proposed device can measure the insulator leakage current and take images of the high-voltage insulation. Yolov5-based models and deep convolutional neural networks (DCCN) are developed to analyze and classify the measured data and estimate the insulator's health condition. We have developed and tested a prototype of the proposed device. The device can issue a real-time warning message when a sudden change takes place in the leakage current value. The control center or smartphones receive the collected data wirelessly. We analyze the transmitted data using the developed methods to detect any anomalies and take appropriate remedial action. The performance and feasibility of the developed device are assessed through extensive experimental analysis. Results attest to the robustness of the proposed device, which is easy to install for existing and future overhead transmission line insulators. © 2024 Elsevier Ltd |
| publisher |
Elsevier Ltd |
| issn |
00457906 |
| language |
English |
| format |
Article |
| accesstype |
|
| record_format |
scopus |
| collection |
Scopus |
| _version_ |
1814778497489436672 |