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 ›› 2025, Vol. 44 ›› Issue (2): 250-255.

• • 上一篇    下一篇

基于改进Apriori算法的地下综合管廊火灾预警技术研究

崔涵, 魏立明   

  1. （吉林建筑大学 电气与计算机学院，吉林 长春 130118）
  • 收稿日期:2023-09-13 修回日期:2024-05-20 出版日期:2025-02-15 发布日期:2025-02-15
  • 作者简介:崔 涵，吉林建筑大学硕士研究生，主要从事火灾自动报警和消防联动控制系统研究，吉林省长春市新城大街 5088 号，130118。
  • 基金资助:
    吉林省科技厅重点研发项目（20230203129SF）；吉林省发展和改革委员会创新能力建设项目（2022C045-3）

Research on fire warning technology for underground comprehensive pipe gallery based on improved Apriori algorithm

Cui Han, Wei Liming   

  1. (School of Electrical and Computer Science, Jilin University of Architecture, Changchun, Jilin 130118, China)
  • Received:2023-09-13 Revised:2024-05-20 Online:2025-02-15 Published:2025-02-15

摘要： 随着城市的快速发展，城市地下综合管廊得以快速建设。由于其主要用于承载城市的电、气、热等资源，因而导致火灾风险大。针对此问题，本文提出一种基于改进Apriori算法的地下综合管廊火灾预警技术。该技术以STM32单片机为主控器，并且采用多种传感器获取管廊内数据。上位机方面采用LabView软件为用户端提供实时的数据监测画面以及报警信息显示。通过试验数据验证所提出的改进算法能够较原算法节省约60%的时间，并且其精确度可以保持在90%以上。针对不同类型火灾需要不同数据挖掘关联规则，本文以地下管廊电气线缆火灾为例，通过PyroSim软件建立火灾模型获取的火灾数据由本文所提算法进行关联规则挖掘，最后得到早期线缆火灾的3个特征，即线缆火灾的预警依据。

关键词: 综合管廊, 火灾预警, 关联规则, Apriori算法, PyroSim

Abstract: With the rapid development of cities, the construction of urban underground comprehensive pipe galleries has been rapidly carried out. Due to its main use to carry urban resources such as electricity, gas, and heat, it has many risk factors and high fire hazards. In response to the above issues, a fire warning and hazard identification system based on the improved Apriori algorithm is proposed in the article. The STM32 microcontroller is used as the main controller and various sensors are used to monitor data inside the pipe gallery in this system. LabView software is adopted as the upper computer to provide real-time data monitoring screens and alarm information display for the user end. Through experimental data verification, the proposed improved algorithm can save about 60% of time compared to the original algorithm, and its accuracy can be maintained at over 90%. For different types of fires that require different data mining association rules, the underground pipe gallery electrical cable fire is taken as an example. The fire data obtained by establishing the fire mode by using PyroSim software is used to mine association rules using the algorithm proposed in this article. Finally, three characteristics of early cable fires are obtained, which are the warning basis for cable fires.

Key words: comprehensive pipe gallery, fire warning, association rules, Apriori algorithm, PyroSim