Proceedings of the 2023 2nd International Conference on Artificial Intelligence, Internet and Digital Economy (ICAID 2023)

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An Identification Method for High Voltage Power Grid Insulator Based on Mobilenet-SSD Network

Authors
Xu Tan1, Fan Yang1, *, Yan Li2, Jinqiao Du2, Yong Yi2, Jie Tian2, Zijun Liu2
1State Key Laboratory of Power Transmission Equipment and System Security and New Technology, School of Electrical Engineering, Chongqing University, Chongqing, 400044, China
2Shenzhen Power Supply Co., Ltd., Shenzhen, 518000, China
*Corresponding author. Email: yangfan@cqu.com
Corresponding Author
Fan Yang
Available Online 28 August 2023.
DOI
10.2991/978-94-6463-222-4_15How to use a DOI?
Keywords
power equipment identification; MobileNet-SSD; insulator; deep learning
Abstract

The identification of power equipment using visible image and deep learning methods has become widespread in the power industry. However, current deep learning algorithms often face issues related to large model parameters and high hardware requirements, making it difficult to integrate them into mobile devices. To overcome these challenges, a novel approach has been proposed to identify insulators on overhead transmission lines using UAVs that carry lightweight models. This method utilizes an enhanced lightweight MobileNet-SSD target detection network, enabling accurate classification and location of power equipment. The results demonstrate that this approach can quickly and precisely label power equipment in complex backgrounds. Additionally, it has small model parameters, high efficiency, strong robustness, and an mAP of 82.47%, making it ideal for enhancing patrol accuracy and real-time monitoring of mobile equipment towards the transmission lines.

Copyright
© 2023 The Author(s)
Open Access
Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

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Volume Title
Proceedings of the 2023 2nd International Conference on Artificial Intelligence, Internet and Digital Economy (ICAID 2023)
Series
Atlantis Highlights in Intelligent Systems
Publication Date
28 August 2023
ISBN
10.2991/978-94-6463-222-4_15
ISSN
2589-4919
DOI
10.2991/978-94-6463-222-4_15How to use a DOI?
Copyright
© 2023 The Author(s)
Open Access
Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

Cite this article

risenwbib
TY  - CONF
AU  - Xu Tan
AU  - Fan Yang
AU  - Yan Li
AU  - Jinqiao Du
AU  - Yong Yi
AU  - Jie Tian
AU  - Zijun Liu
PY  - 2023
DA  - 2023/08/28
TI  - An Identification Method for High Voltage Power Grid Insulator Based on Mobilenet-SSD Network
BT  - Proceedings of the 2023 2nd International Conference on Artificial Intelligence, Internet and Digital Economy (ICAID 2023)
PB  - Atlantis Press
SP  - 160
EP  - 170
SN  - 2589-4919
UR  - https://doi.org/10.2991/978-94-6463-222-4_15
DO  - 10.2991/978-94-6463-222-4_15
ID  - Tan2023
ER  -