A Fault Warning Method for Hotline Tap Clamp Infrared Images Based on Hybrid Segmentation
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- Shen Peifeng
- Taizhou Power Supply Branch, Jiangsu Electric Power Company
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- Yang Yang
- China Electric Power Research Institute
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- Li Lihua
- China Electric Power Research Institute
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- Chen Ting
- Taizhou Power Supply Branch, Jiangsu Electric Power Company
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- Yang Ning
- China Electric Power Research Institute
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抄録
<p>Substation equipment faults are typically related to the heating of equipment components. The hotline tap clamps of substation are critical components for carrying load currents and thermal fault potential. As a result, a new hybrid early warning approach for hotline tap clamp faults in substation equipment is presented. A two-dimensional Otsu algorithm is used to coarse-segment infrared images to minimize the subsequent complexity. Since the Chan–Vese (CV) model is insufficiently accurate for image segmentation with uneven grayscale, then the differential data obtained by the Prewitt operator to identify the goal edges are combined with the CV model to improve segmentation accuracy. The improved CV model achieves excellent segmentation of the hotline tap clamp in the substation. The temperature statistics are utilized for the segmented images, and the hotline tap clamp fault warning is realized based totally on the relative temperature difference. Finally, the experiments exhibit that the method can enhance the segmentation impact of infrared images and obtain the goal of fault warning.</p>
収録刊行物
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- Journal of Advanced Computational Intelligence and Intelligent Informatics
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Journal of Advanced Computational Intelligence and Intelligent Informatics 27 (3), 458-466, 2023-05-20
富士技術出版株式会社
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詳細情報 詳細情報について
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- CRID
- 1390859138435927168
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- NII書誌ID
- AA12042502
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- ISSN
- 18838014
- 13430130
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- NDL書誌ID
- 032826964
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- 本文言語コード
- en
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- データソース種別
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- JaLC
- NDL
- Crossref
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- 抄録ライセンスフラグ
- 使用不可