This paper departs from the more traditional focus of systems with time delays — the loss of stability — to examine an intrinsic benefit of time-delayed systems and a novel approach for parametric identification. For instance, it is well-known that the presence of a time delay will result in an infinite dimensional phase space and can compromise the stability characteristics of a dynamical system. This paper explores the utilization the system higher dimensional transients to provide benefit to the common problem of system identification. Observations are first made about which experimental milling tests can be utilized for parameter identification. A model for the milling experiment is then introduced and a temporal finite element analysis is performed to transform the original delay equations into the form of a dynamic map. Experimental data is then examined with empirical Floquet theory and principal orthogonal decomposition to estimate the reduced order dynamics, or truncated state space dimension, and to identify the empirical Floquet multipliers of the system. Parametric identification is performed through the optimization of model parameters that satisfy the characteristic equation.

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