Distributed computing and sensing for structural health monitoring systems

Structural health monitoring involves automated evaluation of the condition of the structural system based on measurements acquired from the structure during natural or controlled excitation. The data acquisition and the ensuing computations involved in the health monitoring process can quickly become prohibitively expensive with the increase in size of the structure under investigation. In this paper, we propose a distributed sensing and computation architecture for health monitoring of large structures. This architecture involves a central processing unit that communicates with several data communication and processing clusters placed on the structure by wireless means. With this architecture the computation and acquisition requirements on the central processing unit can be reduced. Two different hardware implementations of this architecture one involving RF communication links and the other utilizing commercial wireless cellular phone network are developed. A simple health monitoring experiment that uses neural network based pattern classification is carried out to show effectiveness of the architecture.