Research On Wireless Sensor Network Technology For Uranium Mill Tailing Safety Monitoring

With the increasing demand for nuclear energy,the exploitation and utilization of uranium resources is expanding,resulting in the increasing number of uranium mill tailings,where stored tailings with radioactive nuclides.Once the dam breaks,landslides and radionuclide leaks in the uranium mill tailings,it not only pollutes the environment,destroys the vegetation,endangers the life and health of the surrounding residents,but also brings radiation hazards.So it is necessary to focus on monitoring safe operation state of uranium mill tailings.At present,the monitoring mode and technology level are relatively lagging behind,and can not achieve the effect of dynamic,wireless and long-distance monitoring.This paper uses Wireless Sensor Network(WSN)to realize all time online intelligent monitoring of uranium mill tailings,and studies three sets of key technologies such as routing protocol,data fusion algorithm and positioning technology.The following work is done in this paper.1)Research on an improved routing protocol based on intersecting circle and GAF(IC-GAF).Taking into account the energy constrained characteristics of wireless sensor networks and the needs of uranium tailings safety monitoring,a clustering routing protocol for intersecting circular models is designed.The node arrangement structure of the algorithm is depended on the uranium tailings dam.The monitoring area is divided into a plurality of virtual intersecting circles.The nodes who are divided into a same virtual circle,use this virtual circle as its cluster structure.It selects cluster heads according to given parameters.When the data is transmitted from the cluster head to the base station,the transit nodes in the hot spot around the base station share the transmission to avoid the premature death of the nodes around the base station,so as to balance the energy consumption of the entire network.2)Research on hierarchical data fusion algorithm using event-driven and belief assignment.Through analyzing the requirements of data fusion and the characteristics of uranium tailings safety monitoring data,the algorithm of weighted fusion using Dempster-Shafer(D-S)evidence theory in event driven background is studied.When monitoring the abnormal data in the network,the nodes will enter the high frequency working state(excited state).With the gradual expansion of the event range,a large number of nodes perceive the abnormal data and upload them.By using the D-S evidence theory,the belief assignment function is assigned to the data to fuse data efficiently.In the case of low energy consumption,the amount of data transmission is reduced and the reliability of the data is guaranteed.3)Research on a range-free localization algorithm based on error correction and multi-hop.In order to determine the location of abnormal data in uranium tailings monitoring,combined with the requirement of node positioning accuracy,on the basis of DV-Hop,this algorithm is divided into categories according to the number of hops of the unknown node to the anchor node,and the average distance of each hop is corrected.The distance between the unknown node and the anchor node is obtained by the product of hop and average distance-per-hop.Then the estimation position of unknown node is calculated,and the location error is reduced.Combined with the key technologies mentioned above,a wireless sensor network system for uranium mill tailings with low energy consumption,long network life,reliable data,small positioning error and real-time dynamic monitoring is constructed.