Structural Health Monitoring Based on RealAdaBoost Algorithm in Wireless Sensor Networks

Since frequent accidents such as bridge collapses have drawn much attention, structural health monitoring (SHM) is considered as a research hotspot in both academic and engineering fields. With the development of wireless sensor networks (WSNs), a large number of sensors have been equipped on architectural or mechanical structures to acquire real-time state data that may imply their health problems, which indicates that data processing is of great significance in WSN-based SHM. In this paper, we propose a SHM scheme by using RealAdaBoost algorithm in a WSN-based environment, in which the RealAdaBoost algorithm is employed here for data classification so as to detect and locate damages of the bridge. Simulation results indicate that the proposed RealAdaBoost algorithm provides better performance than several existing ones employed in SHM scenarios.