Experimental study on a general data-based nonlinear identification approach for a MDOF frame model structure

Abstract

Though many system identification methods are currently available for structural physical parameter estimation, a major challenge lies in obtaining reasonably accurate identification results for nonlinear structural systems because the initiation and development of structural damage are typical nonlinear process. Moreover, in most current model updating and identification approaches, structural mass distribution is usually treated as known. But the mass of an engineering structure can not be estimated correctly according to the design drawing directly. In this study, a general data‐based approach using structural dynamic response and excitation measurement time series was proposed and validated for the nonlinear behavior identification of a 4‐story frame structure with smart devices of magneto‐rheological (MR) damper to simulate nonlinear performance. The whole approach includes a two‐stage procedure. In the first stage, least‐squares technique was used to identify the system matrices of an equivalent linear system basing on the impact force applied on each floor of the structure and the corresponding vibration measurements; and in the second stage, the nonlinear restoring force of the MR damper was identified and compared with the measurement with a force gauge. The performance of the proposed approach was studied when current level of 0.15A for the MR damper was employed. Results show that the proposed data‐based approach is capable of identifying nonlinear behavior of engineering structures.