现代电子技术2026，Vol.49Issue(5)：25-29,5.DOI:10.16652/j.issn.1004-373x.2026.05.004
基于改进YOLOv5s的甲烷气体泄漏红外热成像检测方法
Methane gas leakage infrared thermal imaging detection based on improved YOLOv5s
摘要
Abstract
The traditional infrared thermal imaging methane gas leakage detection needs prior background,and it is vulnerable to characteristically similar substance,and its characteristic change is significant under the influence of real-time environmental factors,so a methane gas leakage detection method GAS-YOLOv5s based on YOLOv5s and infrared thermal imaging is proposed.Firstly,the K-means algorithm is used to optimize the pre-categorization of YOLOv5 model anchor whose size is determined by shooting distance and leakage rate.Secondly,the coordinate attention(CA)mechanism is introduced to improve the efficiency of gas feature extraction near the leakage point.Experimental results show that the precision,recall rate,mAP@0.5,and mAP@0.5:0.95 of the improved YOLOv5s model is improved by 6.5%,1.9%,4.8%,and 1.6%,respectively,in comparison with those of the original model.Its detection speed can reach 263 f/s on infrared video test set,which meets the requirement of real-time detection.The results show that the improved YOLOv5s algorithm improves the accuracy rate of infrared thermal imaging methane gas leakage detection,and realizes real-time multi-level classification detection of methane gas,so it can be deployed at various detection terminals.关键词
甲烷气体/红外热成像/气体泄漏检测/坐标注意力/锚框优化/实时检测Key words
methane gas/infrared thermal imaging/gas leakage detection/CA/anchor box optimization/real-time detection分类
信息技术与安全科学引用本文复制引用
冉腾,何丽,杨硕,王仪豪..基于改进YOLOv5s的甲烷气体泄漏红外热成像检测方法[J].现代电子技术,2026,49(5):25-29,5.基金项目
新疆维吾尔自治区重点研发计划项目(2022B01050-2) （2022B01050-2）
