Identification of Civil Engineering Structures using Multivariate ARMAV and RARMAV Models

This paper presents how to make system identification of civil engineering structures using multivariate auto-regressive moving-average vector (ARMAV) models. Further, the ARMAV technique is extended to a recursive technique (RARMAV). The ARMAV model is used to identify measured stationary data from an offshore structure while the recursive RARMAV identification technique is used on simulated data generated by the non-linear finite element program SARCOF modelling a 6-storey 2-bay concrete structure subjected to amplitude modulated Gaussian white noise filtered through a Kanai-Tajimi filter. The results show the usefulness of the approaches for identification of civil engineering structures excited by natural excitatio