In the past decade research into SHM systems has received much attention. One of the emerging and promising approaches is the use of time series analysis. This study develops a method for the assessment of earthquake-induced damage in buildings utilising Autoregressive (AR) time series models and Artificial Neural Networks (ANNs). AR models were applied to the computer simulated seismic response of a linear, lumped mass model of a 3-storey building under different damage conditions. Damage was simulated by a reduction in lateral stiffness at each storey. The AR coefficients were considered to be damage sensitive features of the building's response. ANNs were trained to recognize changes in the patterns of the AR coefficients caused by damage and hence identify and quantify the level of damage at each storey.
|Title of host publication||Progress in Mechanics of Structures and Materials|
|Subtitle of host publication||Proceedings of the 19th Australasian Conference on the Mechanics of Structures and Materials, ACMSM19|
|Publisher||Taylor & Francis|
|Number of pages||6|
|Publication status||Published - 30 Dec 2006|