Research On Monitoring Technology Of Nuclide Migration And Pollution In Uranium Tailings Dam Based On WSN

As the most important structure of uranium tailings pond,uranium tailings dam is a protective barrier for radioactive waste storage site.Once nuclide migration,leakage or dam break occurs,it will cause serious harm to the surrounding environment and people's lives and properties.Therefore,the monitoring of nuclide migration and pollution in uranium tailings dam should be strengthened,and the safety dynamics of uranium tailings dam should be mastered at any time.At present,the monitoring system of uranium tailings dam is relatively backward and poor intelligence,so it is difficult to meet the requirement of continuous automatic monitoring.Wireless sensor network(WSN)is a new monitoring method,which can meet the requirements of automation,low cost,low energy consumption and suitable for monitoring the environment of uranium tailings dam.This paper adopts the WSN technology to monitoring the pollution of nuclide migration in the uranium tailings dam.The routing protocol,data fusion algorithm and location tracking technology in WSN were studied,and the following work was completed:(1)Research on hybrid multi-hop routing protocol for virtual grid.Considering the strip monitoring model of uranium tailings dam and the energy limitation of wireless sensor network,a hybrid multi-hop routing protocol based on virtual grid is designed.The routing protocol uses cellular grid to divide cells,and introduces the optimized threshold functions of node angle ratio,distance ratio and throughput to select cluster heads independently.In the data transmission stage,single hop within cluster and mixed hop between clusters are adopted to prolong the overall network life,effectively reduce the energy consumption of nodes and avoid premature network paralysis.(2)Research on compressed sensing data fusion algorithm.Considering the seasonal monitoring data of nuclide migration in uranium tailings dam and the demand of data fusion,the data fusion algorithm based on improved prediction model and compressed sensing theory is studied.Using the time and spatial correlation characteristics of monitoring data and the outlier eliminating mechanism is used to remove invalid data,prediction model is established to measure monitoring values.The predicted value with high reliability was uploaded to the cluster head,which compressed the data and reconstructed the original data at the Sink node,so as to reduce the overall energy consumption of the network and improve the data reliability.(3)Research on adaptive cuckoo optimal location algorithm.In order to determine the nuclide migration location of uranium tailings dam and its positioning accuracy,an adaptive cuckoo optimization positioning algorithm with mostly error correction is proposed.Firstly,the multi-communication radius of anchor node is used to broadcast the message,and the number of hops is decimated when counting,so as to reduce the error caused by the different length of hops.Then the distance between the node and the anchor node is calculated by using the method of virtual intersecting circular geometry.The mean hop error is reduced by adding weights of each anchor node when the unknown node chooses the mean hop.In order to improve the positioning accuracy,an adaptive search step size cuckoo algorithm is introduced instead of the maximum likelihood estimation method to determine the node coordinates.This paper can provide theoretical refer to WSN application in monitoring nuclide migration and pollution of uranium tailings dam.It can further promote the process of real-time,automatic and intelligent monitoring of uranium tailings dam,improve the safety of uranium tailings dam and reduce the environmental problems of nuclide pollution around tailings dam.