Characteristic nonlinear system identification: A data-driven approach for local nonlinear attachments

Abstract

Abstract This research introduces the characteristic nonlinear system identification (CNSI) procedure for identifying the dynamics of local nonlinear attachments. Unlike many existing methods, the CNSI method requires no prior knowledge or models of the dynamics governing the parent structure or the attachment. Instead, the CNSI technique relies entirely on post-processing of the measured transient response of the attachment and its connection points to the base structure (such that the relative motion can be computed), its mass and a proposed model for its dynamics. The CNSI approach is divided into two phases: a data-processing phase and a model-identification phase. In the first phase, the measured response is post-processed to obtain characteristic displacements and velocities, and instantaneous frequency and damping curves. In the second phase, the analyst proposes a model for the dynamics of the attachment and performs a systematic identification for the unknown parameters using the post-processed data. The result is a reduced-order model, including both nonlinear stiffness and damping, that captures the physics governing the response of the attachment. The CNSI method is demonstrated experimentally using the response of a linear oscillator with a smooth nonlinear attachment.