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Insulators Detection with High Resolution Images | IEEE Conference Publication | IEEE Xplore

Insulators Detection with High Resolution Images


Abstract:

The potential safety hazards for the power grid caused by explosion of insulators occur again and again. Thus, the detecting and monitoring of insulators on the transmiss...Show More

Abstract:

The potential safety hazards for the power grid caused by explosion of insulators occur again and again. Thus, the detecting and monitoring of insulators on the transmission towers is vital. In the paper, a novel method was proposed to detect insulators with high resolution satellites images. First, the SuperView-1 (0.5 m) and WorldView-3 (0.3 m) scenes of Yunnan were gathered, and then gram-schmidt method was used to fusion the original images. Second, a wide deep super resolution network (WDSR) is used to enhance the images resolution by 4 times. Third, fake color output and 1% linear stretched were applied to enhance image detail. Then, an object detection neural network based on feature pyramid networks (FPN) was used to detect transmission tower. Finally, a high-resolution network (HR-Net) was used to detect insulators on the tower. For comparison, three different class weight calculation methods and online hard example mining (OHEM) training methods of HR-Net were also proposed. HR-Net-c2-ohem final achieved highest 0.8001 of F1-Score. Therefore, our proposed method is robust to detect the insulators of transmission line tower with high resolution satellites images.
Date of Conference: 17-22 July 2022
Date Added to IEEE Xplore: 28 September 2022
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ISSN Information:

Conference Location: Kuala Lumpur, Malaysia

References

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