[1]ZHAO Wenqing,CAI Jianying,LI Saichen.Detection of external force damage of transmission lines based on stepwise feature fusion[J].CAAI Transactions on Intelligent Systems,2025,20(5):1082-1092.[doi:10.11992/tis.202406045]
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CAAI Transactions on Intelligent Systems[ISSN 1673-4785/CN 23-1538/TP] Volume:
20
Number of periods:
2025 5
Page number:
1082-1092
Column:
学术论文—机器学习
Public date:
2025-09-05
- Title:
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Detection of external force damage of transmission lines based on stepwise feature fusion
- Author(s):
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ZHAO Wenqing1; 2; CAI Jianying1; LI Saichen1
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1. School of Control and Computer Engineering, North China Electric Power University, Baoding 071003, China;
2. Hebei Province Energy Power Knowledge Calculation Key Laboratory, Baoding 071003, China
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- Keywords:
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external force damage of transmission lines; object detection; feature extraction; stepwise feature fusion; lightweight head; GCIoU loss function
- CLC:
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TP3-05
- DOI:
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10.11992/tis.202406045
- Abstract:
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A detection method based on stepwise feature fusion is proposed to address the challenges posed by instrument deformation under unmanned aerial vehicle (UAV) shooting angles and complex features caused by different operating states of arm-bearing machinery during transmission line inspections. The method integrates deformable large kernel attention networks to extract features from UAV images, performs stepwise feature fusion using a multiscale sequence feature fusion module, and applies lightweight operations to the detection head to reduce the parameters. An gradual complete intersection over union non-max-imum suppression(GCIoU NMS) loss function further enhances the model. Experiments on a self-constructed dataset show mAP50% and mAP50%-95% improvements of 10.5 and 10.2 points, reaching 86.8% and 58.4%, respectively. On the VOC dataset, mAP50% and mAP50%-95% increased by 7.3 and 8.1 points to 79.5% and 58.8%, respectively. The results demonstrate the effectiveness of the method for external force damage detection of transmission lines in complex environments.