A Comparative Study on the Identification of Building Natural Frequencies based on Parametric Models

Tarek Edrees Saaed, George Nikolakopoulos, and Jan-Erik Jonasson


System Identification, Structural Health Monitoring, Modal Identification Techniques, Structural Behaviour


The analysis and design of civil engineering structures is a complex problem, which is based on many assumptions to simplify these operations. This in turn, leads to a differ- ence in the structural behavior between calculations based models and real structures. Structural identification was proposed by many researchers as a tool to reduce this dif- ference between models and actual structures. Moreover, Parametric models and non-parametric models were used intensively for system identification by many researchers. In this research effort, the system identification concept is utilized to identify the natural frequencies for a steel build- ing’s frames. Different black box linear parametric mod- els such as Transfer Function model (TF), Auto-Regressive model with eXternal input model (ARX), Auto-Regressive Moving Average with eXternal input (ARMAX) model, Output Error model structure (OE), and Box-Jenkins model (BJ) were examined for identifying the first 10th natural frequencies for the building’s frames, based on simulation results. Abaqus 6.12 finite-element software was utilized to perform the time history analysis for the examples and the obtained responses at one point of the roofs (assumed as a sensor) were further processed by the parametric mod- els to obtain the building’s natural frequencies based on the Abaqus time history analysis results (assumed as a mea- surements). After that, Abaqus 6.12 was utlized again to perform another analysis, which is called frequency anal- ysis to obtain the building’s natural frequencies and mode shapes based on the stiffness and mass (not the measure- ments) of the buildings. The results showed that the linear parametric models TF, ARX, ARMAX, OE, and BJ are ro- bust to identify the natural frequencies of building and they are recommend for future work.

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