火灾早期AI探测系统—阻止电池存储区灾情研究  

Early Fire AI Detection System-Research on Preventing Disaster in Battery Storage Area

作　　者：赵金月 ZHAO Jinyue(Fire Rescue Detachment of Zhengzhou City,Zhengzhou 450001,China)

机构地区：[1]河南省郑州市消防救援支队,河南郑州450001

出　　处：《通信电源技术》2023年第4期83-85,89,共4页Telecom Power Technology

摘　　要：为进一步研究电池存储区火灾早期灾情探测的及时性和准确性,基于锂电池存储区火灾原因及火灾因子,认为人工智能(Artificial Intelligence,AI)技术融入探测系统中能够同时兼顾火情探测的实时性和精准性。试验验证结果证实,基于AI技术的火灾探测器对白雾的响应时间显著优于感烟探测器,对及早发现和阻止电池存储区灾情蔓延具有重要意义。In order to further study the timeliness and accuracy of disaster detection in the early stage of fire in battery storage area,based on the causes and factors of fire in lithium battery storage area,it is considered that Artificial Intelligence(AI)technology is integrated into the detection system,which can give consideration to the real-time and accuracy of fire detection at the same time.The experimental verification results show that the response time of fire detector based on AI technology is significantly better than that of smoke detector,which is of great significance for early detection and prevention of disaster spread in battery storage area.

关 键 词：火灾早期 人工智能(AI)技术 探测系统 锂电池存储区 

分 类 号：TM912[电气工程—电力电子与电力传动]