Nonlinear System Identification of a Multi-story Building with Geometrical Nonlinearity Using a Deterministic Output-Only-Data Approach

Nonlinear system identification based on output-only data is challenging since the stochastic approaches require the structure to be excited by random input with a uniform Gaussian distribution. This chapter applies a deterministic output-only approach to the parameter estimation of a linear multi-story specimen with an amplitude-dependent geometrical nonlinearity. The approach is independent of the input type, value, and number but requires the excitation to be applied away from the nonlinearity. The vibration responses to high-amplitude excitations are taken into a subspace-based identification algorithm that simultaneously yields both nonlinear and underlying linear parameters. The process is verified by comparing the underlying linear parameters with the linear modal parameters of the structure under low-amplitude excitation. The results indicate a superior accuracy of the estimated parameters in the simulation and an acceptable confidence range for the experimental test.