DSC-SeNet: Unilateral Network with Feature Enhancement and Aggregation for Real-Time Segmentation of Carbon Trace in the Oil-Immersed Transformer

DSC-SeNet: Unilateral Network with Feature Enhancement and Aggregation for Real-Time Segmentation of Carbon Trace in the Oil-Immersed Transformer

Large oil-immersed transformers have metal-enclosed shells, making it difficult to visually inspect the internal insulation condition. Visual inspection of internal defects is carried out using a self-developed micro-robot in this work. Carbon trace is the main visual characteristic of internal insu...

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Bibliographic Details
Main Authors: Liqing Liu, Hongxin Ji, Junji Feng, Xinghua Liu, Chi Zhang, Chun He
Format: Article
Language:English
Published: MDPI AG 2024-12-01
Series:Sensors
Subjects:
oil-immersed transformer
discharge carbon trace
semantic segmentation
deformable convolution
canny edge detection
real-time processing
Online Access:https://www.mdpi.com/1424-8220/25/1/43
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