Title: Real-time detection system of bird nests on power transmission lines based on lightweight network

Authors: Haopeng Yang; Enrang Zheng; Yichen Wang; Junge Shen

Addresses: School of Electrical and Control Engineering, Shaanxi University of Science and Technology, Xi'an, Shaanxi, China ' School of Electrical and Control Engineering, Shaanxi University of Science and Technology, Xi'an, Shaanxi, China ' Unmanned System Research Institute, Northwestern Polytechnical University, Xi'an, Shaanxi, China ' Unmanned System Research Institute, Northwestern Polytechnical University, Xi'an, Shaanxi, China

Abstract: In response to real-time detection requirements for bird nests and other hidden danger on power grid transmission lines, this paper proposes a lightweight real-time detection system of bird nests. In terms of bird nests on transmission towers, there are many small targets, which may lead to possible loss of data. Thereby, the algorithm detects small targets of bird nests through three scales: low, middle and high scales. At the same time, the DIoU-NMS calculation method is utilised to make the prediction box closer to the real box. The average accuracy of the improved algorithm is 90.05%, 7.38% higher than the original one. The detection speed of the detection system of bird nests in NVIDIA Xavier NX, an embedded device, is 26.3 FPS. With higher detection accuracy and real-time detection speed, the requirements of high-precision and real-time inspection of State Grid in line inspection can be met.

Keywords: bird nests detection; lightweight network; multi-scale fusion; attention mechanism; non-maximum suppression.

DOI: 10.1504/IJWMC.2023.131295

International Journal of Wireless and Mobile Computing, 2023 Vol.24 No.3/4, pp.217 - 225

Received: 08 Sep 2021
Accepted: 07 Mar 2022
Published online: 06 Jun 2023 *

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