Complex time series modeling and analysis for rotor dynamics identification

Abstract

A new time series method, directional ARMAX (dARMAX) model-based approach, is proposed for rotor dynamics identification. The dARMAX processes complex-varied signals, utilizing the complex modal resting theory which enables the separation of the backward and forward modes in the two-sided frequency domain and makes effective modal parameter identification possible, to account for the dynamic characteristics inherent in rotating machinery. The dARMAX is superior in nature to the conventional ARMAX particularly in the estimation of the modal parameters for isotropic and weakly anisotropic rotors. Numerical simulations are performed to demonstrate effectiveness of the dARMAX.