Research On Data Aggregation Of Wireless Sensor Networks For Structural Health Monitoring System

Wireless sensor network (WSN) consists of smart sensors which form a multi-hop self-organized network by radio communications in area monitored. The information of the sensor field collected and processed by the sensors cooperatively is send to terminate. WSN have lots of advantages, such as the low cost, high precision, fault tolerance, remote control. It is easy to diagnose and repair. WSN had been widely used in structural health monitoring and Damage location system as a result of advantages such as low-cost, high-precision, fault-tolerance, remote control, diagnosed and repaired easily, and in target tracking, and automatic target identification as well.The Data Aggregation adopted of WSN in common Routing Protocol is investigated in this paper. Then Multi-Sink Data Aggregation Routing based on time synchronization (MSDAR) is put forward to resolve data sharing and data aggregation when there are overlaps in target-areas.(1) The data aggregation mechanism now available is classified and Data Aggregation of routing aggregation used in Directed Diffusion , LEACH,PEGASIS is compared in this paper.(2) After analyzing the Structural Health Monitoring System on Bridge and tunnels, a simple data-aggregation algorithm is analyzed in detail, which is based on Data-Centric Routing in order to save energy consume in WSN and ensure the data collected as well as promoting the efficiency in structural health monitoring system.(3) Modify and improve the data-aggregation algorithm in MSDAR to resolve data sharing and data aggregation of nodes in overlapping-target-areas, so as to adapt multi-sink aggregation.(4) Comparing with two classic routing protocols, DD and PEGASIS, the simulation results demonstrate that the improved MSDAR saves significant energy. Especially when there are overlaps in target-areas the energy consume is very low and the lifetime of WSN is prolonged obviously, based on the impact of density of sensors and interval on consumption and time-delay in MSDAR through simulation analysis by NS2 simulator.