Distribution Network Component Positioning Methods Based on Multi-Modal Image Information

doi:10.3969/j.issn.1008-0198.2024.06.012

Hunan Electric Power ›› 2024, Vol. 44 ›› Issue (6): 83-89.doi: 10.3969/j.issn.1008-0198.2024.06.012

• New Technology and Application • Previous Articles Next Articles

Distribution Network Component Positioning Methods Based on Multi-Modal Image Information

HUANG Zhihong^1,2, YAN Xingyu³, TAO Yan⁴, ZHANG Hui³, XU Xianyong¹

1. State Grid Hunan Electric Power Company Limited Research Institute, Changsha 410208, China;
2. Hunan Xiangdian Test and Research Institute Co., Ltd., Changsha 410208, China;
3. School of Robotics,Hunan University, Changsha 410082, China;
4. School of Electrical and Information Engineering, Changsha University of Science and Technology,Changsha 410114, China

Received:2024-07-29 Revised:2024-09-04 Online:2024-12-25 Published:2024-12-25

Abstract

Abstract: A multi-modal image component localization method for distribution network inspection is proposed for the task of thermal fault discrimination of distribution network components. The method includes two key steps that is multi-modal image information coordination and object detection. Firstly, a self-adaptive image registration method is proposed to address the issue of misalignment between high-resolution visible light images and infrared images with temperature information,which can complete high-quality cross modal registration tasks. Secondly,the prediction information of the registered visible image is transferred to the infrared image by the prediction information transfer method to complete the detection of the infrared image. The results show that compared with direct detection of infrared images,the proposed method can improve detection accuracy by 18.4% and performs extremely well in terms of precision and recall.

Key words: electrical inspection, image registration, object detection, multimodal, deep learning

CLC Number:

TM727

HUANG Zhihong, YAN Xingyu, TAO Yan, ZHANG Hui, XU Xianyong. Distribution Network Component Positioning Methods Based on Multi-Modal Image Information[J]. Hunan Electric Power, 2024, 44(6): 83-89.

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Distribution Network Component Positioning Methods Based on Multi-Modal Image Information

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