主管：中华人民共和国应急管理部
主办：应急管理部天津消防研究所
ISSN 1009-0029  CN 12-1311/TU
消防科学与技术

消防科学与技术 ›› 2021, Vol. 40 ›› Issue (2): 238-241.

• • 上一篇    下一篇

小空间火灾多元探测装置和实现方法研究

薛莹1,2，刘建翔1,2，赵志鹏1,2，李绍鹏1,2，刘欣1,2，殷艳华1,2   

  1. 1. 齐鲁工业大学(山东省科学院)，山东济南250014；2. 山东省科学院自动化研究所，山东济南250014
  • 出版日期:2021-02-15 发布日期:2021-02-15
  • 通讯作者: 刘建翔（1977-），男，山东省科学院自动化研究所副研究员。
  • 作者简介:薛莹（1979-），女，山东菏泽人，山东省科学院自动化研究所助理研究员，硕士,主要从事气体探测、火焰探测和消防机器人的研究，山东省济南市历下区科院路19 号，250014。
  • 基金资助:
    山东省科学院—新泰市产学研协同创新基金项目(2019-CXY28)；山东省科学院—兰山区产学研协同创新基金项目(2018XY-18)

Research on multisensor fire detection device and realization method in small space

XUE Ying1,2, LIU Jian-xiang1,2, ZHAO Zhi-peng1,2, LI Shao-peng1,2, LIU Xin1,2, YIN Yan-hua1,2   

  1. 1. Qilu University of Technology (Shandong Academy of Sciences), Shandong Jinan 250014, China; 2. Institute of Automation, Shandong Academy of Sciences, Shandong Jinan 250014, China
  • Online:2021-02-15 Published:2021-02-15

摘要：

针对小空间火灾探测方法单一、误报漏报率高、采集数据处理简单的问题，提出1 种小空间火灾多元探测装置及方法，能够实现对火灾的烟雾、CO 气体、温度、火焰等的多元探测，多角度多方位采集火灾信号，利用信息融合技术和算法，寻找特征信息之间的规律，对数据信息进行分析解析、优化组合，运用人工神经网络和模糊推理方法，采取反复的样本训练将探测数据的误差降到最低，从而准确地判断火灾所处的阶段和类型，及时有效地采取灭火抑制措施。研究结果证明，小空间火灾多元探测方法能够满足小空间的火灾探测要求，减少了公共财产的损失，对火灾探测的进一步研究具有重要意义。

关键词: 小空间, 火灾探测, 多元探测, 人工神经网络, 模糊推理, 信息融合

Abstract:

Aiming at the problems existing in small space fire detection,such as single detection method, high false alarm rate and simple data collection and processing method, a multisensor detection device and method are proposed. The detection device can realize multi- angle or multi- directional collection of fire signals including fire smoke, CO gas, temperature, flame, etc. Using information fusion technology and algorithms, the law between characteristic information is found, to analyze and optimized group the data information. Using the method of artificial neural networks and fuzzy inference, the error of detection datais minimized byrepeated sample training, so as to determine the stage and type of the fire, andtake fire extinguishing measures promptly and effectively. The studies have proved that the multisensor fire detection devices and methods can meet the requirements for fire detection in small spaces, reducing the loss of public property, and have important significance for the further research of fire detection.

Key words: small space, fire detection, multivariate detection, artificial neural network, fuzzy inference, information fusion