安全、健康和环境2024，Vol.24Issue(4)：1-6,6.DOI:10.3969/j.issn.1672-7932.2024.04.001
基于YOLOv5的加油站火灾视频图像智能识别
Intelligent Recognition of Fire Video Image in Gas Station Based on YOLOv5
摘要
Abstract
In view of the possible problems such as slow response of early open flame identification in the current on-site monitoring and early warning process of gas stations,more than 100 000 cases of fire image dataset were constructed through on-site simulation experiments and network acquisition,the YOLOv5s neural network structure was improved,and an early flame target detection model suitable for petrochemi-cal gas stations and other scenes was developed.The experimental results showed that the improved model had improved in recognition accuracy,recall rate and average recognition accuracy,etc.Random sampling of fire accident images of gas stations for effect testing can achieve 100%recognition accuracy and 96%re-call rate.On this basis,the intelligent monitoring platform of early fire of gas station was constructed to provide effective early warning support for emergency fire response under sudden fire.关键词
YOLOv5/目标检测/早期火灾/深度学习/智能识别/加油站/火灾视频Key words
YOLOv5/object detection/early fire/deep learning/intelligent identification/gas station/fire video分类
信息技术与安全科学引用本文复制引用
姜春雨,赵祥迪,王振中,刘馨泽..基于YOLOv5的加油站火灾视频图像智能识别[J].安全、健康和环境,2024,24(4):1-6,6.基金项目
中国石油化工股份有限公司十条龙项目(321114),第一代人工智能加油站成套技术. （321114）
