河北水利电力学院学报2025，Vol.35Issue(3)：22-29,8.DOI:10.16046/j.cnki.issn2096-5680.2025.03.004
基于YOLOv5算法的水电厂检修工器具识别系统研究
Identification of Maintenance Tools and Instruments for Hydropower Plants Based on YOLOv5 Algorithm
摘要
Abstract
With the introduction of the concept of smart power plants,the traditional management mode of hydropower plants is gradually transitioning towards a smart management system.Based on the current management status of maintenance tools in hydropower plants,and combined with the rapid devel-opment of deep convolutional neural network technology in the field of image recognition in recent years,especially with the increasingly mature object detection technology,a tool recognition system based on YOLOv5 neural network model is proposed,aiming to achieve accurate recognition of maintenance tools in hydropower plants.The system utilizes calibration tool data.And the collected data is divided into training set,validation set,and testing set,which are used for neural network training,model validation,and per-formance evaluation,respectively.The training results show that the system displays excellent recognition ability with precision(P),recall(R),and mean average values(mAP)of 90.3%,72%,and 83.4%,in-creased by 2.1%,1.6%and 1.3%,respectively compared to the original model.Further testing is con-ducted on the trained network using the validation set,and the test results show that the system can accu-rately identify the types of tools,automatically generating visualized anchor frames during the recognition process.And it accurately displays the coordinates and confidence of anchor frames.This feature not only improves the efficiency of access and retrieval work,but also enhances the accuracy and convenience of tool management.The system has demonstrated high recognition accuracy and stability,providing strong tech-nical support for the intelligent management of hydropower plants.关键词
水电厂/YOLOv5/算法模型/工器具识别Key words
hydroelectric plant/Yolov5/algorithm model/tool recognition分类
信息技术与安全科学引用本文复制引用
陈铁华,吴广新,许明,王艺瑶,杨智文..基于YOLOv5算法的水电厂检修工器具识别系统研究[J].河北水利电力学院学报,2025,35(3):22-29,8.基金项目
吉林省科技厅重点研发项目(20230203154SF) （20230203154SF）
国网吉林省电力有限公司松原供电公司项目(SGJLSYO0KJS2200906) （SGJLSYO0KJS2200906）
