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2024 | OriginalPaper | Chapter

Development and Application of Edge Intelligent Monitoring Device for Hidden Danger of Transmission Channel Based on AI Chip

Authors : Zhen Wang, Yanjie Hu, Ziquan Liu, Hai Xue, Xueqiong Zhu

Published in: The Proceedings of the 18th Annual Conference of China Electrotechnical Society

Publisher: Springer Nature Singapore

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Abstract

Tower cranes, excavators and other external damage hazards lead to frequent transmission channel accidents. Effectively detecting the external damage hazards around the transmission channel is of great significance to ensure the safe and stable operation of the transmission line. Therefore, based on the edge intelligent chip, an intelligent edge detection device for the hidden danger of transmission channel is developed, and a lightweight hidden danger identification method suitable for the front-end device with limited computing resources is proposed. Firstly, the visual feature of the transmission channel image is extracted by using the depth residual network, and then the candidate area of the hidden danger target is captured by using the candidate area production network RPN, Then the full convolution neural network FCN is used to classify and locate the hidden danger of external damage. Finally, the actual collected transmission channel images are constructed into a sample set for model test and experimental verification. The experimental results show that the proposed method shows good applicability in the edge device.

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Liu, L., et al.: Line-tree distance measurement and tree barrier early warning technology based on satellite remote sensing monitoring. Southern Power Syst. Technol. 15(08), 130–138 (2021). (in Chinese)

Yourui, H., Lingya, J., Tao, H.: High-accuracy insulator defect detection for overhead transmission lines based on improved YOLOv. Appl. Sci. 12(24), 12682 (2022)CrossRef

Gu, X., Tang, D., Huang, X.: Defect detection and recognition of power grid inspection images based on deep learning. Power Syst. Protect. Control 49(5), 91–97 (2021). (in Chinese)

Chen, J., Yu, Y., Chen, Z., Han, W.: An improved method for defect identification of transmission lines based on YOLOv3. Southern Power Syst. Technol. 15(1), 114–120 (2021). (in Chinese)

Sun, Y., Liao, S., Gao, C.: Weakly supervised instance segmentation based on two-stage transfer learning. IEEE Access 8, 24135–24144 (2020)CrossRef

Ma, F., Wang, B., Dong, X., Wang, H., Luo, P., Zhou, Y.: Power vision edge intelligence: power depth vision acceleration technology driven by edge computing. Power Syst. Technol. 44(06), 2020–2029 (2020). (in Chinese)

Liu, Z., Miu, X., Chen, J.: Research review on intelligent processing of visible image for overhead power line inspection. Power Syst. Technol. 44(03), 1057–1069 (2020). (in Chinese)

Yang, J., Qin, Z., Pang, X.: Detection and identification method of foreign body intrusion in transmission lines based on deep learning network. Power Syst. Protect. Control 49(4), 37–44 (2021). (in Chinese)

Wei, X., Lu, W., Zhao, W., Wang, D.: Research on detection method of transmission lines against external breach based on improved Mask R-CNN. Power Syst. Protect. Control 49(23), 210482 (2021). (in Chinese)

10.

Sun, C., Cai, W., Jiao, B.: Research on a target detection method for external breakage prevention of transmission lines based on I-OHEM. Electric. Automat. 42(04), 103–106 (2020). (in Chinese)

11.

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12.

Law, H., Deng, J.: CornerNet: detecting objects as paired keypoints. Int. J. Comput. Vision 28(3), 642–656 (2020)CrossRef

13.

Deng, L., Zhang, J., Xu, G., Zhu, H.: Infrared small target detection via adaptive M-estimator ring top-hat transformation. Pattern Recogn. 112, 107729 (2021)CrossRef

Title: Development and Application of Edge Intelligent Monitoring Device for Hidden Danger of Transmission Channel Based on AI Chip
Authors: Zhen Wang
Yanjie Hu
Ziquan Liu
Hai Xue
Xueqiong Zhu
Publisher: Springer Nature Singapore
Book: The Proceedings of the 18th Annual Conference of China Electrotechnical Society
Print ISBN: 978-981-9710-63-8

Electronic ISBN: 978-981-9710-64-5

Copyright Year: 2024
DOI: https://doi.org/10.1007/978-981-97-1064-5_73