基于LabVIEW的校园宿舍消防安全管理系统的设计与实现

发布时间：2018-04-28 03:57

本文选题：智能消防管理系统 + ZigBee无线网络　；参考：《电子科技大学》2014年硕士论文

【摘要】：校园是一个人口密集区,而且宿舍是学生居住和活动的重要场所之一,人员具有很强的流动性和密集性,如果学生在宿舍违规使用大功率电器,就会电路的承载的功率过大,容易引发火灾,一般情况下,火灾发生前,都会产生大量的烟雾,建立监控宿舍烟雾系统,能够对火灾的发生进行防范。在当前阶段,传感技术、无线通信技术的飞速发展为我们的智能消防管理系统的更新和换代提供了坚实的技术保障,而本文的研究正是在这样的技术背景之下,针对如何提高消防管理系统智能水平的问题进行了重点研究,以期望能够降低误报率和漏报率。在本文的研究中,首先对当前阶段国内外无线监测网络的实际应用情况进行了系统的分析,并梳理了主要的研究成果,选择了适用于宿舍智能消防管理系统的ZigBee无线监控网络,根据高校宿舍楼实际情况设计并构建了无线智能消防管理系统通信网络,并根据具体的系统设计的要求,选择合适的烟雾与火光控制进行烟雾控制管理。最终以BP神经网络算法作为火灾探测算法,该算法在实际的应用过程中具有容错性强、误差率小、故障率低的特点,能够对多种不同类型的火灾数据进行及时而有效的处理,以此为基础来判定火灾的实际情况。然后介绍了虚拟仪器的应用情况,并对LabVIEW的特点进行了重点分析,本研究中应用LabVIEW虚拟仪器开发了BP神经网络算法,除此之外也设计并实现了一套以神经网络算法为基础的火灾自动报警虚拟系统,并构建了宿舍火灾识别模型,并且对其进行了仿真实验和火灾模拟实验,在完成整个实验工作之后,其结果充分表明,该算法可以有效解决火灾探测灵敏度与误报率之间的矛盾,达到了预期的效果。应用LabVIEW开发的无线智能消防管理系统具有可靠性高、故障率低等特点,但是还是存在一些有待完善的地方,所以文章的最后对该系统提出了一些改善的方法,并对它的发展作出了展望。
[Abstract]:Campus is a densely populated area, and dormitories are one of the most important places for students to live and activities. The personnel are highly mobile and dense. If students violate the use of high-power electrical appliances in dormitories, they will carry too much power. It is easy to cause fire. Generally, a large amount of smoke will be produced before the fire, and the smoke system of monitoring dormitory can be established to prevent the fire. At the present stage, the rapid development of sensing technology and wireless communication technology has provided a solid technical guarantee for the renewal and replacement of our intelligent fire control management system, and the research of this paper is under such a technical background. This paper focuses on how to improve the intelligence level of fire control management system in order to reduce false alarm rate and false alarm rate. In the research of this paper, firstly, the actual application of wireless monitoring network at home and abroad at present stage is systematically analyzed, and the main research results are combed, and the ZigBee wireless monitoring network suitable for dormitory intelligent fire control management system is selected. According to the actual situation of university dormitory, the communication network of wireless intelligent fire control management system is designed and constructed. According to the requirements of system design, appropriate smoke and fire control are selected for smoke control and management. Finally, the BP neural network algorithm is used as the fire detection algorithm. The algorithm has the characteristics of strong fault tolerance, low error rate and low failure rate in the actual application process. It can deal with many different types of fire data in a timely and effective manner. This is the basis for judging the actual situation of the fire. Then the application of virtual instrument is introduced, and the characteristics of LabVIEW are analyzed. In this study, BP neural network algorithm is developed by using LabVIEW virtual instrument. In addition, a set of fire automatic alarm virtual system based on neural network algorithm is designed and implemented, and the fire identification model of dormitory is constructed, and the simulation experiment and fire simulation experiment are carried out. The experimental results show that the algorithm can effectively solve the contradiction between the sensitivity of fire detection and the false alarm rate and achieve the desired results. The wireless intelligent fire control management system developed by LabVIEW has the characteristics of high reliability and low failure rate, but there are still some problems to be improved. The prospect of its development is also given.
【学位授予单位】：电子科技大学
【学位级别】：硕士
【学位授予年份】：2014
【分类号】：TU892;TP311.52

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