Zhou Lixing

Weight optimized centroid localization algorithm on radioactive pollution monitoring by WSN for uranium tailings

Aiming at the problem of high cost of cable layout and poor maintenance in traditional radioactive pollution monitoring for uranium tailings, considering banded dam and little node connectivity, a weight optimized centroid localization algorithm is proposed. Under different index, by comparing the positioning accuracy and the influence of the external disturbance, new algorithm changes the index of weight and measured distance -1 to -1.5, resulting in an accuracy improvement in long distance. Simulation demonstrated that compared with centroid localization algorithm and maximum likelihood estimation, average positioning error of the new algorithm was reduced by 37.5% and 30.7%, and the maximum positioning error was reduced by 1/5 and by 2/5. With high reliability and stability, the new algorithm can meet the requirements of position in radioactive pollution monitoring for uranium tailings.

Data fusion in deep mine safety monitor based on Markov optimized unbiased gray system

The natural conditions of the deep mine are especially poor and deployment of wireless sensor networks in it is constrained by limited energy and communication resources, Aiming at this problem, a data fusion algorithm based on unbiased gray Markov prediction is proposed to solve this problem. This algorithm uses the unbiased gray Markov prediction model to predict the future data and set the threshold, If the error of the predicted value is within the threshold range, do not send the data, due to the environment in deep coal mine usually relatively stable, so we can reduce the energy consumption by reducing the upload data by using the forecast data. Simulation results shows that the data transfer rate can be reduced under the same threshold, while reducing the energy consumption and extending the network usage time.

Research of cluster routing algorithm in cellular grid by tracking radionuclide contamination of uranium trailings impoundment

In order to solve energy-consumption of wireless transmission route, a clustering routing protocol based on improved cellular model is proposed for environmental monitoring through wireless sensor network (WSN) of nuclide leakage in uranium tailings impoundment. The protocol sets the virtual partition of the cellular structure in the monitoring area to reduce complexity of the cluster and to balance the network energy consumption in clustering way. Considering angle ratio and distance ratio between the centroid of the virtual partition and the node when choosing the cluster head, node communication in cluster adopts the method of mixing hop to realize energy balance. Simulation results show that this protocol is not only prolonging the network lifetime effectively, but reducing its energy consumption.

An event-driven high-precision data fusion algorithm based on double-layer clustering

In order to ensure the high accuracy of data fusion in the real-time online monitoring of environmental parameters, an event-driven, high-precision data fusion algorithm based on double-layer clustering is proposed in wireless sensor network (EDDCHA). EDDCHA algorithm based on feature extraction in depth learning model and traditional structure clustering routing, established the general event and emergency event double-layer cluster routing model, distinguished the cluster priority order, set the emergency threshold, and realized double-layer cluster Head synchronization data fusion. The simulation results show that EDDHA algorithm can obtain more accurate fusion data in real time under the condition of similar energy consumption and SAEMDA algorithm.

Radial increment WSN routing algorithm in deep mine

A radial increment WSN routing algorithm(RIRA) is proposed to reduce energy consumption and improve transmission efficiency caused by complex environment and narrow tunnel of deep mine, in which the wired network layout is limited. Multi-hop routing methods between clusters can reduce energy consumption. A weighting formula is constructed to select cluster heads, the greater the weight, the more likely to become the final cluster head. The smaller the cluster near Sink, the more the number of clusters, which can share data to the Sink by a number of cluster heads, effectively balancing the energy consumption and ensuring the reliability of data transmission. The simulation results show that the RIRA algorithm can delay the death time of the first node, balance cluster head energy, prolong the network lifetime, and improve robustness of the network.

WSN monitoring area partition clustering routing algorithm for energy-balanced

In order to optimize the energy-balanced problem and lengthen the network lifetime for Wireless sensor network(WSN) monitoring, a routing protocol that based on monitoring area partition clustering for energy-balanced(EBPC) was proposed. We divided monitoring area into several virtual partitions, controlled the number of common nodes and clusters by data fusion rate, and forwarded cluster heads data to the next partitions with minimum path selection coefficient. Through performance analysis and simulation of EBPC reaches a conclusion that EBPC routing protocol has a superior balance of energy consumption than LEACH and EEUC, when data fusion rate is 0.5, network lifetime lengthen rate well be 1.3, and the effect of EEUC is more obvious when the data fusion rate have a lower value.