Fire detection using vision transformer on power plant

被引：6

作者：

Zhang, Kaidi ^{[1
]}

Wang, Binjun ^{[1
]}

Tong, Xin ^{[1
]}

Liu, Keke ^{[2
]}

机构：

[1] Peoples Publ Secur Univ China, Sch Informat & Cyber Secur, Beijing 100038, Peoples R China

[2] Yunnan Univ Finance & Econ, Kunming 650000, Yunnan, Peoples R China

来源：

ENERGY REPORTS | 2022年 / 8卷

关键词：

Deep learning; Fire detection; Power plant; Vision transformer; CONVOLUTIONAL NEURAL-NETWORKS; SURVEILLANCE;

D O I：

10.1016/j.egyr.2022.05.224

中图分类号：

TE [石油、天然气工业]; TK [能源与动力工程];

学科分类号：

0807 ; 0820 ;

摘要：

The importance of power plant safety is increasing in the era of gradual technological development. When a fire occurs in the power plant, it will cause huge material losses, social unrest, and even casualties. The paper studies the common methods and models of fire warning, and introduces several model recognition techniques based on flames or smoke. Improved an automated power plant identification system based on the vision transformer, and proved the advantages of the technology through comparative analysis. (C) 2022 Published by Elsevier Ltd.

引用

页码：657 / 664

页数：8

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