Transmission Line Object Detection Method Based on Label Adaptive Allocation

Lijuan Zhao, Chang’an Liu, Zheng Zhang and Hongquan Qu
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Lijuan Zhao: School of Control and Computer Engineering, North China Electric Power University, Beijing 102206, China
Chang’an Liu: School of Information, North China University of Technology, Beijing 100144, China
Zheng Zhang: School of Information, North China University of Technology, Beijing 100144, China
Hongquan Qu: School of Information, North China University of Technology, Beijing 100144, China

Mathematics, 2022, vol. 10, issue 12, 1-14

Abstract: Inspection of the integrality of components and connecting parts is an important task to maintain safe and stable operation of transmission lines. In view of the fact that the scale difference of the auxiliary component in a connecting part is large and the background environment of the object is complex, a one-stage object detection method based on the enhanced real feature information and the label adaptive allocation is proposed in this study. Based on the anchor-free detection algorithm FCOS, this method is optimized by expanding the real feature information of the adjacent feature layer fusion and the semantic information of the deep feature layer, as well as adaptively assigning the label through the idea of pixel-by-pixel detection. In addition, the grading ring image is sliced in original data to improve the proportion of bolts in the dataset, which can clear the appearance features of small objects and reduce the difficulty of detection. Experimental results show that this method can eliminate the background interference in the GT (ground truth) as much as possible in object detection process, and improve the detection accuracy for objects with a narrow shape and small size. The evaluation index AP (average precision) increased by 4.1%. Further improvement of detection accuracy lays a foundation for the realization of efficient real-time patrol inspection.

Keywords: transmission line object; detection method; enhanced real feature information; label adaptively allocation; FCOS (search for similar items in EconPapers)
JEL-codes: C (search for similar items in EconPapers)
Date: 2022
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