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For the shortcomings of the traditional wired way for structure health monitoring, a structure health monitoring (SHM) for bridge based on wireless sensor network (WSN) is proposed. The S-Mote node used for the WSN is designed and implemented which meets the specific hardware requirements of the structural health monitoring and supports the TinyOS as its operating system. The SHM system is deployed and tested on the ZhengDian Viaduct Bridge. In this deployment, 6 nodes are distributed over the main span, collecting the ambient vibrations at 100Hz. The collected data agrees with theoretical models and theoretical value of the bridge. [ABSTRACT FROM AUTHOR]

As large amount of energy constrained nodes are randomly distributed in network, the entire lifetime of wireless sensor network is difficult to estimate. In this paper, a back propagation (BP) neural network based Markov model is presented to calculate the lifetime of wireless sensor network. BP neural network is employed to reduce the calculation difficulty of Markov state equation. The simulation results indicate that this method gives the value of maximum lifetime exactly and its computing complexity is low. The quantitative degree of computing reliability relative error between the results of three layer BP neural network and the Markov model is 10− 4. [ABSTRACT FROM AUTHOR]