Cluster-based energy-efficient structural health monitoring using wireless sensor networks

Recent years have witness booming interests of using wireless sensor networks (WSNs) for structural health monitoring (SHM). In a WSN, it has been widely regarded that wireless data transmission is one of the most energy consuming operations. To address the limitations of wireless sensor nodes in terms of power supply, in-network processing has been regarded as an effective way to decrease the energy consumption. However, it should be noted that many SHM algorithms are computationally intensive. If not handled well, it is quite possible that the energy consumed in in-network processing is even larger than that in transmitting the raw data. In this paper, we choose a classic damage detection algorithm and tailor it for WSNs. Moreover, the deployed wireless sensor nodes are divided into clusters to minimize the overall energy consumed during in-network processing and wireless transmissions. The effectiveness of the cluster-based approach is evaluated by simulation and experiment.