Structural Identification of Partially Nonlinear System Subjected to Seismic Excitation Using Intelligent Parameter Varying (IPV) Approach

摘要

Restoring forces in civil structures subject to strong earthquake can exhibit highly non-linear characteristics, thus accurate non-linear system identification is critical. Parametric system identification approaches are commonly used, but these require a priori knowledge of restoring force characteristics. Non-parametric approaches do not require this a priori information, but they typically lack direct associations between the model and the system dynamics. The authors have been developing Intelligent Parameter Varying (IPV) system identification technique for health monitoring and damage detection. This technique overcomes the limitations of traditional parametric and non-parametric approaches, while preserving the unique benefits of each. This paper presents the application of IPV techniques to partially nonlinear structural system subjected to seismic excitation. For more effective use of IPV and the flexibility on sensor location, modified version of IPV technique embedding prediction error method to estimated the characteristics of the linear part, combined with Radial Basis Function (RBF) network to estimate the constitutive characteristics of restoring forces in the nonlinear part, are applied to structural system identification. Simulation results demonstrate the effectiveness of IPV in identifying partially non-linear system characteristics, using fewer sensors, with minimum priori information, while preserving a direct association with the structural dynamics.