Abstract：The security of the bridge could be effectively improved by monitoring and evaluation on its healthy status.Since there are too many parameters in the bridge’s monitoring,which are complex and difficult,it is actually hard to obtain a relatively accurate assessment of the bridge health status using the simple and traditional method.To integrate different types of parameters and asynchronous data,and get conformity assessment of the bridge health status,we proposed an assessment method of bridge health status,based on two-level neural network integration.Our method was verified to reduce the complexity of multi-source monitoring data fusion process and improve the accuracy of the bridge health assessment by the simulation calculations.
2012, Vol. 36 
