物联网安全监测系统的设计优化与关键技术的研究与应用

发布时间：2018-05-03 06:04

本文选题：实时监测 + 无线传感器　；参考：《华北科技学院》2017年硕士论文

【摘要】：煤矿安全生产问题一直是国家和政府重点关注的问题。对煤矿井下作业环境进行实时监测,是预防煤矿事故发生、提高煤矿安全管理的重要手段之一。随着物联网技术的发展,其在工业领域的应用越来越广泛。研究表明,煤矿井下特殊地质条件和恶劣环境十分适合将无线传感器技术与煤矿安全监测监控系统结合起来,成为提高煤矿安全监测监控是实时性、有效性的重要手段。本文针对煤矿生产作业环境中的灾害危险因素,分析了目前基于无线传感器的实时监控系统,提出了基于无线传感器网络的煤矿井下环境监测的设计方案,并根据系统的可靠性保障机制,提出了一种适合煤矿安全监测的三维均匀物联网节点部署方法。在保障监测数据准确的基础上,本文进一步研究了提高物联网拓扑可靠性的相关机制,有节点之间的距离冗余、簇头节点的非等量备份冗余、基站向管理中心传输数据的基站并联冗余和传输方式三冗余,并对相关的参数进行了量化分析。根据多源信息处理技术,利用动态限幅滤波对监测数据进行预处理,然后用最优加权算法对数据进行数据级融合,最后利用灰色关联分析和粗糙集理论属性约简的特点,形成了基于模糊粗糙-灰色关联的决策级融合算法,实现对煤矿安全监测监控系统的数据进行有效处理。从理论分析和仿真的结果看,本文中所提出的节点部署方式和可靠性保障机制具有监测区域覆盖程度高、能耗均衡和灵活、可扩展等特点,对提高煤矿安全监测的拓扑可靠性具有显著效果。通过粗糙集理论、模糊集理论、灰色关联分析的联合,为煤矿环境监测数据处理提供了一个新的途径,同时又可以广泛的应用于其他复杂环境的评估。
[Abstract]:The problem of coal mine production safety has always been the focus of attention of the state and the government. It is one of the important means to prevent coal mine accidents and improve coal mine safety management to monitor the working environment of underground coal mines in real time. With the development of Internet of things technology, its application in industrial field is more and more extensive. The research shows that the special geological conditions and the bad environment are very suitable to combine the wireless sensor technology with the coal mine safety monitoring and monitoring system and become an important means to improve the real time and effectiveness of coal mine safety monitoring and monitoring. Aiming at the disaster risk factors in coal mine production environment, this paper analyzes the real-time monitoring system based on wireless sensor, and puts forward the design scheme of underground environment monitoring based on wireless sensor network. According to the reliability guarantee mechanism of the system, a three dimensional uniform Internet of things node deployment method suitable for coal mine safety monitoring is proposed. On the basis of ensuring the accuracy of monitoring data, this paper further studies the related mechanisms to improve the topological reliability of the Internet of things, including the distance redundancy between nodes, the non-equal backup redundancy of cluster head nodes, and the relative mechanism of improving the topology reliability of the Internet of things. The parallel redundancy of the base station and the three redundancy of the transmission mode of the base station transmitting data to the management center are analyzed, and the related parameters are analyzed quantitatively. According to the multi-source information processing technology, the dynamic amplitude limiting filter is used to preprocess the monitoring data, and then the optimal weighting algorithm is used for data level fusion. Finally, the characteristics of grey correlation analysis and attribute reduction of rough set theory are used. A decision level fusion algorithm based on fuzzy rough and grey correlation is developed to effectively process the data of coal mine safety monitoring and monitoring system. From the theoretical analysis and simulation results, the proposed node deployment and reliability guarantee mechanism have the characteristics of high coverage of monitoring area, balanced and flexible energy consumption, extensible, etc. It has remarkable effect on improving the topological reliability of coal mine safety monitoring. The combination of rough set theory, fuzzy set theory and grey correlation analysis provides a new way for data processing of coal mine environmental monitoring, and can be widely used in other complex environment evaluation.
【学位授予单位】：华北科技学院
【学位级别】：硕士
【学位授予年份】：2017
【分类号】：TD76;TP274

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