微型电脑应用2025，Vol.41Issue(4)：1-3,7,4.
基于YOLOV网络的隧道火灾检测与应用
Tunnel Fire Detection and Application Based on YOLOV Network
摘要
Abstract
Tunnel fires cause traffic interruption,and in severe cases may endanger the safety of personnel,property and tunnel structure.The current fire detection algorithms cannot effectively detect the interfence such as flickering lights in the tunnel monitoring perspective.This paper proposes a tunnel fire video object detection dataset,and uses the YOLOV network that combines multiple frames for object detection to obtain the fire detection results,and performs statistics on the change rate of the flame smoke area to reduce the false alarm of fire and improve the detection results reliability.Experiments on actual fire videos in various tunnels show that the proposed method achieves average detection accuracy of 90.53％and detection speed of 26.75 f/s.The proposed method can identify flames that are far away from the camera,distinguish multiple types of lights and other distractors,and has higher detection reliability and practical application values.关键词
高速公路隧道/隧道火灾检测/火灾检测数据集/深度网络/视频目标检测Key words
expressway tunnel/tunnel fire detection/fire detection dataset/deep network/video object detection分类
天文与地球科学引用本文复制引用
王向前,孟修建,梁浩翔,文雅,宋焕生..基于YOLOV网络的隧道火灾检测与应用[J].微型电脑应用,2025,41(4):1-3,7,4.基金项目
国家自然科学基金(6207072223) （6207072223）
