面向伴生金属矿放射性污染监测的无线传感器网络关键技术研究

So many radioactive minerals such as uranium, thorium and radon which come from decay of uranium and thorium are existed in coexisting metallic ore. Those substances are very harmful to environmental so it is essential to study the pollution behavior of radioactive Minerals in order to control effectively their hazardous. For obtaining the comprehensive and accurate radioactive pollution data, a new real-time monitoring system with wireless sensor network is proposed. Tradition wireless sensor network is constrained by energy. So in the harsh environment the network nodes are very easy to be failure or malfunction. The defect can easily split the whole connective network topology and results in the forming of network isolated island. At final rate of the whole network coverage is reduced. To solve the flaw of tradition wireless sensor network, the concept of small-world theory is introduced. Some key features of wireless sensor network under Small-world network such as network architecture, modeling technique, energy variation, and mobile node positioning technique will be studied in a deep-going way. Optimal design of new generation wireless sensor network topology as well as its positioning mechanism is also discussed in our project. Based on above work, a new radioactive pollution monitoring and re-warning platform will be established in order to solve the defeat of tradition system in the complex environment. The new platform will not only contribute to exploring the physical and chemical properties of coexisting metallic ore and pollution behavior of radioactive mineral, but also provides scientific basis for solving radioactive pollution from uranium, thorium and radon in coexisting metallic ore.

伴生金属矿中含有大量的铀、钍及其衰变产生的氡及子体，严重污染自然环境，为全面有效地获取放射性环境污染数据，研究其污染行为、有效控制放射性环境污染，本项目针对无线传感器网和现有放射性污染监测系统不能在恶劣环境下实时监测的缺陷，研究基于小世界理论的无线传感器网的体系结构与建模技术，分析小世界网络作用下无线传感器网能量变化规律及移动节点定位技术，探索新型的无线传感器网最优拓扑控制技术和定位机制，在此基础上构建放射性污染监测和预警平台，解决传统的放射性辐射监测系统在野外复杂环境下不能实时监测的不足，探索伴生金属矿放射性元素的理化特性和污染行为，为解决伴生金属矿中的铀、钍及子体产生的放射性环境污染这一重大需求提供科学依据。

针对现有辐射污染监测系统中存在的监测范围有限、机动能力差、环境场数据分布不均衡等缺点，本项目基于核辐射环境安全与耐久性监测的要求，采用和无线传感网络结合的新方法，同时利用小世界理论高集聚系数和低平均路径的优势，设计基于小世界理论的无线传感器网络拓扑控制和定位机制，建立小世界网络模型及其评价体系，研究基于无线传感器网络的智能环境预警架构和实现方法。.提出了一种新的基于小世界理论的拓扑控制算法(TLWA)，该算法利用小世界理论较高的聚集系数和较短的平均路径长度的特点，在网络中构建了高级节点层和普通节点层的层次拓扑结构，减少节点的能耗，最大可能的提高网络的生存周期。设计了一种依赖于TLWA算法的拓扑结构的路由算法(RALT)，RALT算法的核心思想是利用TLWA拓扑结构中的长程链接，信息通过高级节点来传递，通过高级节点网中的长程链接来大大缩短信息路由所需的跳数，从而减少普通节点的能耗且路由效率更加高效。提出了一种基于复杂网络理论的无线传感器网络分簇算法，使得网络的拓扑结构更加清晰，优化了节点的路由选择。提出一种新的簇首选择算法，簇内任意一个节点每轮结束后距离剩余能量最大的节点较近且距离汇聚节点最短的为簇首。针对低锚节点密度的WSN网络提出一种自主择优的蒙特卡洛定位算法(PWMCB)，基于锚盒子信息，自主筛选出高精度的优质节点，用以辅助其他普通节点定位。.数据采集与处理软件利用定时器获取单位时间或单位深度的地下各单元的数据，对现场数据显示、放射性测井曲线输出等功能。通过对实测数据进行分析处理，从而明确伴生放射性矿山开采过程中及退役治理后如何有效的减少矿山污染源对环境的污染，减轻国家对伴生金属矿放射性辐射危害防护及退役治理工作中的经济压力。.项目实施期间，项目成员共发表论文9篇，录用1篇，其中收录8篇；获批实用新型专利11项，申请发明专利7项，授权3项；获得软件著作权1项，培养了12名硕士研究生。