Application Research Of WSN Based On Data Fusion In Smart Grid

The wireless sensor network is characterized by low cost,low energy consumption and strong expansion capability.Applied to transmission line monitorin g,it can be done without manual intervention,reducing system construction and operating costs.In the application scenario of the wireless sensor network in the condition monitoring of the transmission line,the survival time of the network needs to be long.But sensor nodes are typically powered by tiny batteries,and the battery can provide very limited energy.Therefore,the data fusion and clustering routing algorithm are introduced into the transmission line state monitoring network,which can improve data transmission efficiency and reduce network energy consumption.In this paper,based on the acquisition and transmission of transmission line condition monitoring data,a node energy optimization algorithm based on node energy and distance between nodes is proposed.By introducing the distance threshold to avoid the generation of long chain and reduce the hop count of data transmission.The appropriate cluster head node is selected according to the remaining energy of the battery carried by the nodes in the cluster and the distance between the nodes.After the selected cluster head works for a period of time,when the remaining energy of the battery carried reaches the set threshold,a new round of cluster head selection process is started,and a new cluster head node is selected in time.The energy consumption levels of each node are similar,thus prolonging the life cycle of the transmission line monitoring network.In this paper,the data fusion method combining D-S evidence theory and BP neural network is used to process the data in the cluster head node.The BP neural network algorithm has self-learning,can perform distributed processing and does not require prior information,and performs multi-channel sensor data fusion.The feature layer and the decision layer are combined to make full use of the advantages of BP neural network and D-S evidence theory.The output of BP neural network is used as evidence of D-S evidence theory.The key information of the security state is based on the current security status of the node,and the probability of a security incident may be inferred in the future.Based on the proposed routing algorithm,MATLAB is used to simulate the experiment.By comparing the performance of different routing algorithms in the energy consumed by the network,the amount of data transmission and the number of nodes surviving,it can be concluded that the routing algorithm proposed in this paper can reduce the data transmission of nodes.Energy consumption,expand the data transmission capacity of nodes,and extend the life of the network.It has certain reference significance for the transmission protocol applied in the transmission line monitoring network.