火灾预警中基于YOLO V5的火源智能检测定位方法  

Intelligent detection and location method of fire source based on YOLO V5 in fire warning

作　　者：张旭彤 胡鹏 赵鑫 丁云霞 ZHANG Xutong;HU Peng;ZHAO Xin;DING Yunxia(College of artificial intelligence,Anhui University of Science and Technology,Huainan 232000,China)

机构地区：[1]安徽理工大学人工智能学院,安徽淮南232000

出　　处：《微电子学与计算机》2023年第3期67-74,共8页Microelectronics & Computer

基　　金：安徽高校自然科学研究重点项目(KJ2020A0289);安徽理工大学青年教师科学研究基金重点项目(QNZD2021-02);安徽省大学生创新训练项目(S202210361271);安徽理工大学科研基金(13210679);淮南市科技规划项目(2021005)。

摘　　要：如何高效地检测出火灾初期的火源并对其进行准确定位,是有效遏制火情恶化和及时制定消防计划的重要前提.目前火源检测定位所面临的主要问题为火源检测与定位双任务相互分离,这严重制约了火灾预警的实时性.为了克服上述问题,提出以YOLO V5作为火源检测基础模型,同时利用CIOU(Complete intersection over union)损失函数对anchor(anchor-boxes)与GT(Ground Truth)进行精准框定以进一步提高模型标注精度,并将Leaky RELU激活函数替换为正则化和激活函数相结合的GELU(Gaussian Error Linear Unit).另外,在准确检测出火源的同时,采用平行双目定位算法对火源进行空间定位,以实现火源检测与定位的智能一体化.实验结果表明,所提方法的火源检测mAP值比原始算法提高了9.8%,在保证检测火源精确性的同时能准确定位火源位置.How to detect the fire source efficiently and accurately locate it is an important prerequisite for effectively controlling the deterioration of fire situation and making fire control plan in time.At present,the main problem faced by fire source detection and location is that the dual tasks of fire source detection and location are separated from each other,which seriously restricts the real-time performance of fire early warning.To overcome the above problems,YOLO V5 is proposed as the basic model of fire source detection,and CIOU(Complete intersection over union)loss function is used to accurately frame anchor(anchor-boxes)and GT(Ground Truth)to further improve the annotation accuracy of the model.The leaky RELU activation function is replaced by GELU(Gaussian Error Linear Unit),which combines regularization and activation function.In addition,while accurately detecting the fire source,the parallel binocular location algorithm is used to locate the fire source in space,to realize the intelligent integration of fire source detection and location.The experimental results show that the fire source detection map value of the proposed method is 9.8%higher than the original algorithm,which can accurately locate the fire source while ensuring the accuracy of fire source detection.

关 键 词：目标检测 YOLOV5 双目定位 火源检测 智慧消防 

分 类 号：TP391.4[自动化与计算机技术—计算机应用技术]