无线电工程2024，Vol.54Issue(6)：1584-1594,11.DOI:10.3969/j.issn.1003-3106.2024.06.030
变电站多尺度异常入侵目标轻量化检测方法
Lightweight Detection Method for Multi-scale Anomaly Invasion Targets in Substations
摘要
Abstract
The construction concept of smart grids has determined the trend of unmanned monitoring of anomaly invasion targets in suburban substations,promoting the rapid development of intelligent detection methods for anomaly invasion targets in substations.However,at present,there is no dataset specifically designed for anomaly invasion targets in this scenario,and the existing target detection methods have not been optimized for lightweight design on the edge computing end of substations,which is not suitable for real-time monitoring of substation edge devices that require round-the-clock monitoring.To address these issues,starting from practical application requirements,a Dataset for Anomaly Invasion Targets in Substations(SAITD)is constructed,and a lightweight anomaly invasion target detection network,YOLOv5-Substation,which is suitable for substation edge detection devices is proposed based on the YOLOv5s model.A micro-scale target feature extraction layer and an upsampling lightweight operator CARAFE are added to expand the receptive field while fully preserving the semantic information of multi-scale targets in the feature map,improving the detection accuracy of the original model from the architecture end.Based on the knowledge distillation model,the original model is lightweighted using Network-slimming strategies to ensure the detection accuracy of the original model while accelerating model inference.Simulation experiments show that the accuracy of the lightweighted edge-end computing model is 3.3％higher than that of YOLOv5s,and the inference speed is 41.9％faster,providing a strong data foundation,technical support and security guarantee for the full-speed operation of smart grids.关键词
异常入侵目标检测/网络剪枝/知识蒸馏/边缘计算平台/轻量化模型Key words
anomaly invasion target detection/Network-slimming/knowledge distillation/edge computing platform/lightweight model分类
信息技术与安全科学引用本文复制引用
潘磊,赵枳晴,傅强,郑远,田俊..变电站多尺度异常入侵目标轻量化检测方法[J].无线电工程,2024,54(6):1584-1594,11.基金项目
中国民用航空飞行学院智慧民航专项(ZHMM2022-005) （ZHMM2022-005）
民航飞行技术与飞行安全重点实验室开放基金(FZ2022KF10) （FZ2022KF10）
民航飞行技术与飞行安全重点实验室自主研究项目(FZ2022ZZ06) （FZ2022ZZ06）
中国民用航空飞行学院重点面上项目(ZJ2021-11) （ZJ2021-11）
中国民用航空飞行学院2023研究生创新项目(X2023-29)Smart Civil Aviation Project of Civil Aviation Flight University of China(ZHMM2022-005) （X2023-29）
Open Foundation of Key Laboratory of Flight Techniques and Flight Safety,CAAC(FZ2022KF10) （FZ2022KF10）
Independent Research Project of Key Laboratory of Flight Techniques and Flight Safety,CAAC(FZ2022ZZ06) （FZ2022ZZ06）
Key Projects of Civil Aviation Flight University of China(ZJ2021-11) （ZJ2021-11）
Postgraduates Innovation Project of Civil Aviation Flight University of China(X2023-29) （X2023-29）
