基于数据融合的隧道火灾监控方法研究与应用
发布时间：2018-12-14 06:15
【摘要】：随着社会经济的快速发展,城市化建设发展越来越迅速,城市公路交通在其中扮演着愈来愈重要的作用,其中隧道的作用在交通工程中占有不可忽视的地位。城市隧道是城市道路的重要组成部分,是根据城市地形特点和城市交通建设现状,为了缓解交通拥堵,方便市民出行而修建的一段城市公路隧道。武汉这几年规划并且建成了不少城市隧道,包括已经投入使用的武汉长江隧道、水果湖隧道、八一路隧道、中山路隧道、黄龙山隧道以及在建的东湖隧道等等。这些隧道的投入使用一定程度上缓解了武汉的交通压力,显著提高了武汉市民的通行效率,促进了武汉的经济发展。本文依托武汉市八一路隧道为课题背景,从火灾监控系统的国内外研究现状出发,总结了国外隧道火灾报警监控系统的优点,分析了国内火灾报警监控系统的缺点与不足,并提出了具体的实现解决方案。同时分析了隧道火灾诊断中常用的传感器并对它们进行了分类,在此基础上研究了各类传感器输出信息的形式,并获得更为准确可靠的火灾状况估计。本文首先介绍了数据融合的意义以及相应的层次结构,同时分析介绍了几个主要的数据融合算法(如Bayes方法、D-S推理法等),接着介绍了火灾监控系统中相应的传感器的种类以及其输出信息的形式,以及对决策层融合目标识别中的不确定性信息进行分类并指出了相应的处理方法,包括不确定性信息处理方法和集成方法;接着具体介绍隧道监控系统中多传感器的融合问题,并提出具体实现融合的方案,同时将D-S证据理论和BP神经网络技术应用到该融合方案中,并进行实际的数据融合算法仿真分析,发现该理论能够有效去除整体数据中的异常数据,对火灾监控系统的联动准确性的提高有较明显的改善。最后本论文将城市隧道智能监控系统以系统策略控制层、信息采集与处理层、传感器控制层、传感器物理层的四层架构进行实现,并利用基于D-S证据理论技术应用于火灾监控的实际项目中,并详细设计和实现了城市隧道监控的火灾报警系统。
[Abstract]:With the rapid development of social economy and the rapid development of urbanization, urban highway traffic plays a more and more important role, and the role of tunnel plays an important role in traffic engineering. Urban tunnel is an important part of urban road. It is a section of urban highway tunnel which is built according to the characteristics of urban topography and the present situation of urban traffic construction in order to alleviate traffic congestion and make it convenient for citizens to travel. Wuhan has planned and built many urban tunnels in recent years, including the Wuhan Yangtze River Tunnel, the Shuiguo Lake Tunnel, the Bayi Road Tunnel, the Zhongshan Road Tunnel, the Huanglong Mountain Tunnel and the East Lake Tunnel under construction. The use of these tunnels to some extent alleviates the traffic pressure in Wuhan, improves the traffic efficiency of Wuhan citizens, and promotes the economic development of Wuhan. Based on the research background of Bayi Road Tunnel in Wuhan, this paper summarizes the advantages of foreign tunnel fire alarm monitoring system, and analyzes the shortcomings and shortcomings of the domestic fire alarm monitoring system. And put forward the concrete realization solution. At the same time, the sensors commonly used in tunnel fire diagnosis are analyzed and classified. On this basis, the output information of all kinds of sensors is studied, and more accurate and reliable fire condition estimation is obtained. This paper first introduces the significance of data fusion and the corresponding hierarchical structure. At the same time, several main data fusion algorithms (such as Bayes method, D-S reasoning method, etc.) are analyzed and introduced. Then it introduces the types of sensors and the form of output information in the fire monitoring system, classifies the uncertain information in decision level fusion target recognition, and points out the corresponding processing methods. Including uncertain information processing method and integration method; Secondly, the problem of multi-sensor fusion in tunnel monitoring system is introduced in detail, and the scheme to realize the fusion is put forward. At the same time, D-S evidence theory and BP neural network technology are applied to the fusion scheme. The simulation analysis of the actual data fusion algorithm shows that the theory can effectively remove the abnormal data from the whole data and improve the linkage accuracy of the fire monitoring system obviously. Finally, the intelligent monitoring system of urban tunnel is implemented in four layers: system strategy control layer, information acquisition and processing layer, sensor control layer and sensor physical layer. Based on D-S evidence theory technology, the fire alarm system of urban tunnel monitoring is designed and implemented in detail.
【学位授予单位】：武汉理工大学
【学位级别】：硕士
【学位授予年份】：2015
【分类号】：U458
[Abstract]:With the rapid development of social economy and the rapid development of urbanization, urban highway traffic plays a more and more important role, and the role of tunnel plays an important role in traffic engineering. Urban tunnel is an important part of urban road. It is a section of urban highway tunnel which is built according to the characteristics of urban topography and the present situation of urban traffic construction in order to alleviate traffic congestion and make it convenient for citizens to travel. Wuhan has planned and built many urban tunnels in recent years, including the Wuhan Yangtze River Tunnel, the Shuiguo Lake Tunnel, the Bayi Road Tunnel, the Zhongshan Road Tunnel, the Huanglong Mountain Tunnel and the East Lake Tunnel under construction. The use of these tunnels to some extent alleviates the traffic pressure in Wuhan, improves the traffic efficiency of Wuhan citizens, and promotes the economic development of Wuhan. Based on the research background of Bayi Road Tunnel in Wuhan, this paper summarizes the advantages of foreign tunnel fire alarm monitoring system, and analyzes the shortcomings and shortcomings of the domestic fire alarm monitoring system. And put forward the concrete realization solution. At the same time, the sensors commonly used in tunnel fire diagnosis are analyzed and classified. On this basis, the output information of all kinds of sensors is studied, and more accurate and reliable fire condition estimation is obtained. This paper first introduces the significance of data fusion and the corresponding hierarchical structure. At the same time, several main data fusion algorithms (such as Bayes method, D-S reasoning method, etc.) are analyzed and introduced. Then it introduces the types of sensors and the form of output information in the fire monitoring system, classifies the uncertain information in decision level fusion target recognition, and points out the corresponding processing methods. Including uncertain information processing method and integration method; Secondly, the problem of multi-sensor fusion in tunnel monitoring system is introduced in detail, and the scheme to realize the fusion is put forward. At the same time, D-S evidence theory and BP neural network technology are applied to the fusion scheme. The simulation analysis of the actual data fusion algorithm shows that the theory can effectively remove the abnormal data from the whole data and improve the linkage accuracy of the fire monitoring system obviously. Finally, the intelligent monitoring system of urban tunnel is implemented in four layers: system strategy control layer, information acquisition and processing layer, sensor control layer and sensor physical layer. Based on D-S evidence theory technology, the fire alarm system of urban tunnel monitoring is designed and implemented in detail.
【学位授予单位】：武汉理工大学
【学位级别】：硕士
【学位授予年份】：2015
【分类号】：U458
【参考文献】
相关期刊论文 前10条
1 张，
本文编号：2378074
本文链接：https://www.wllwen.com/kejilunwen/daoluqiaoliang/2378074.html
