An experimental study on distributed damage detection algorithms for structural health monitoring

Distributed structural damage detection has become the subject of many recent studies in Structural Health Monitoring (SHM). Development of smart sensor nodes has facilitated the growth of this concept enabling decentralized data processing capabilities of nodes whose sole responsibility once was acquisition of data. An experimental study has been carried out on a two span reinforced concrete slab in this paper. Different crack damages are created by the static loads and the impact tests that are carried out on the slab. Two damage detection and localization methods, one based on Auto Correlation Function-Cross Correlation Function (ACF-CCF) and the other on Auto Regressive (AR) time series model are used to detect damage from measured responses. The results from the two methods are compared in order to determine which method has been more effective and reliable in determining the damage to the concrete structure.