水力发电2026，Vol.52Issue(2)：91-101,11.
基于改进YOLOv5m的水电厂工器具识别系统研究
A Power Plant Maintenance Tool Recognition System Based on Improved YOLOv5m
摘要
Abstract
To address the need for rapid and accurate identification of tools during the borrowing and returning process in hydropower plants,as well as to prevent the issues of incorrect or missed borrowing,a tool dataset named Tool-Data is established,and a lightweight detection algorithm based on an improved YOLOv5m is proposed.This method replaces the original feature extraction network with MobileNetV3 and substitutes the conventional convolutional modules in the original network with optimized cross-stage depthwise separable convolutional modules,aiming to reduce the number of parameters and computational load of the network.Meanwhile,the SE attention mechanism is introduced to mitigate background interference,thereby enhancing the model's recognition accuracy for small and medium-sized targets.Furthermore,the anchor box dimensions are re-optimized based on the K-means clustering algorithm,and the Mosaic data augmentation technique is improved.The adoption of the DIOU_NMS algorithm increases the accuracy of filtering bounding boxes and reduces the rate of missed detections for small targets.Experimental results on the Tool-Data dataset show that the improved YOLOv5m achieves precision,recall and mean average precision(mAP)values of 90.5%,89.28%and 93.38%,respectively,on the tool detection dataset,which are 0.55,18.24 and 10.94 percentage points higher than those of the original YOLOv5m.The enhanced YOLOv5m lightweight model meets the requirements for high efficiency and precision in tool identification under complex conditions during the borrowing and returning process.关键词
工器具/YOLOv5m/SE注意力机制/K-means算法/轻量化网络/Mosaic数据增强Key words
tools and equipment/YOLOv5m/SE attention mechanism/K-means algorithm/lightweight network/Mosaic data augmentation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,何锫,邹颜泽,袁敬懿..基于改进YOLOv5m的水电厂工器具识别系统研究[J].水力发电,2026,52(2):91-101,11.基金项目
吉林省科技厅重点研发项目(20230203154SF) （20230203154SF）
国电电力发展股份有限公司和禹水电开发公司科研项目(220240163) （220240163）
