Establishment and application of basic information database for fire scene reconstruction

Fire Science and Technology ›› 2021, Vol. 40 ›› Issue (2): 284-287.

Previous Articles Next Articles

Establishment and application of basic information database for fire scene reconstruction

LIU Bo1, LI Li-ming1, XING Ao1, YAO Hao-wei2

1. Shenyang Fire Science and Technology Research Institute of MEM,Liaoning Shenyang 110034, China; 2. School of Architectural Environmental Engineering, Zhengzhou University of Light Industry, Henan Zhengzhou 450002, China

Online:2021-02-15 Published:2021-02-15

Abstract

Abstract: This paper expounds the importance and necessity of the basic information database for fire scene reconstruction, and emphatically introduces the data composition of this database. Based on the basic data from this database, fire scene reconstruction of one case is realized. The database established in this paper can improve the accuracy and reliability of fire scene reconstruction and assist in judging the correctness and rationality of fire accident investigation.

Key words: fire protection, fire scene reconstruction, fire load, database

LIU Bo, LI Li-ming, XING Ao, YAO Hao-wei. Establishment and application of basic information database for fire scene reconstruction[J]. Fire Science and Technology, 2021, 40(2): 284-287.

[1]	Ding Yifei, Lv Xin, Cheung Wai Kit, Zhang Yuxin, Huang Xinyan. Digitized fire load survey of office building: data collection and statistical analysis [J]. Fire Science and Technology, 2025, 44(2): 152-155.
[2]	Peng Lei, Qiu Peifang, Ou Jiajia. Experimental study on fire spread between timber structure buildings [J]. Fire Science and Technology, 2024, 43(7): 959-966.
[3]	Luo Jing, Tong Yanmin, Li Li, Liu Zhaofeng, Xia Mingjun, Fu Daoxian. Fire load statistics and analysis of wood-framed traditional villages in Lijiang Stone Town [J]. Fire Science and Technology, 2024, 43(11): 1537-1542.
[4]	Li Guangyao, Sun Zhenwen, Zhu Jun, Zhang Guannan. Database construction and application of hazardous chemical explosion and fire accidents [J]. Fire Science and Technology, 2023, 42(4): 577-581.
[5]	YUAN Chun, SUN Shou-kuan. Application of smart firefighting internet of things system in fire investigation [J]. Fire Science and Technology, 2021, 40(2): 296-298.
[6]	SHI Wen-lin, LIU Dong-feng, WU Xi-hui. Analysis and discussion on some problems of government information disclosure of fire and rescue organizations [J]. Fire Science and Technology, 2021, 40(2): 267-270.
[7]	YU Zi-xuan, SHE Jun-yi, KONG Xiao-xu MENG Guo-dong, CHENG Yong-hong. Research of block-type self-extinguishing apparatus for electric cabinet based on thermal insulation material [J]. Fire Science and Technology, 2021, 40(2): 245-251.
[8]	WANG Xiao-hui, RONG Jian-hua, YANG Xiang-qian. Research on thermal simulation method of lithium battery based on monomer simplification [J]. Fire Science and Technology, 2021, 40(1): 81-84.
[9]	ZHANG Mei - hong, SONG Jian - jiang. Reflection on the fire safety countermeasures of residential buildings from the 2019-nCoV epidemic [J]. Fire Science and Technology, 2020, 39(7): 1013-1015.
[10]	YE Xiao - man , , HE Qi - ze , ZHAO Hua - liang , LI Xiao - lian . Survey and statistical analysis of fire load in super five - star hotel rooms [J]. Fire Science and Technology, 2020, 39(7): 942-945.
[11]	SUN Nan-nan, LIU Jian-min, XU Hui, LIANG Qiang. Analysis of internal temperature distribution characteristics in combustion training room [J]. Fire Science and Technology, 2020, 39(5): 692-696.
[12]	CHEN Tao, HU Cheng, BAO Zhi-ming, FU Xue-cheng, WANG Rong-ji, XIA Jian-jun. Comparison of the fire extinguishing performance of different types of compressed gas foam on class B fires [J]. Fire Science and Technology, 2020, 39(5): 645-648.
[13]	LIU Qing-en. Performance-based fire protection design of a large public transportation hub [J]. Fire Science and Technology, 2020, 39(5): 633-636.
[14]	LI Si-cheng, BI Shao-ying. Revelation of international Halon Bank on China's national Halon management and recycling system [J]. Fire Science and Technology, 2020, 39(12): 1762-1765.
[15]	CHEN Zhao-hui, CHEN Zhi-yu. Research and application of residual network model based on artificial intelligence for smoke detection [J]. Fire Science and Technology, 2020, 39(12): 1747-1750.

Establishment and application of basic information database for fire scene reconstruction

PDF (PC)

Knowledge

Abstract

Cite this article

share this article

References

Related Articles 15

Recommended Articles

Metrics

Comments