变电站鸟巢自动检测系统设计与实现

Design and Implementation of Automatic Substation Bird Nest Detection System

针对变电站鸟巢影响站内设备及电网安全运行的问题,基于变电站自动巡检技术构建一种鸟巢检测系统。根据变电站鸟害特征及鸟巢在站内分布特性,制订工程点位配置标准,并使用多尺度特征融合策略建立鸟巢检测模型。鸟巢具有隐蔽性强、结构复杂多样的特点,为此从小目标、设备遮挡和光线变化等方面展开强化学习。在40座220 kV变电站进行工程应用测试,结果表明所提出的检测系统检出量高于人工巡视检出量12倍,可有效识别多种设备场景的鸟巢,且对隐蔽性鸟巢具有较好的泛化能力,有效填补了人工巡视的时空盲区。

Aiming at the problem that the bird nests in the power substation threaten the stable operation of the equipment and the power grid,this paper studies the construction of a substation bird nest automatic detection system based on substation automatic inspection technology.According to the characteristics of bird damages and the distribution characteristics of bird nests in the power substations,it formulates the engineering point configuration standard and uses a multi-scale feature fusion strategy to establish a bird nest detection model.Due to the strong concealment and complex structures of the bird nest,the paper carries out reinforcement learning for equipment occlusion,light changes,and small targets.The engineering application test was carried out in 40 substations with a voltage level of 220 kV.The results show that the detection volume of the proposed method is 12 times higher than that of manual inspection,which can effectively identify bird nests in various equipment scenarios,and has a good generalization ability for hidden bird nests.This study fills the time-space blind spot of manual inspection.