Estimating turbogenerator foundation parameters: model selection and regularization

Estimating a model of the foundation of large machines, such as turbogenera tors, is vital for tasks such as fault diagnosis and modal balancing. Unfor tunately, it is rarely possible to perform a modal test on the foundations without the rotor present. This paper considers a method to estimate a foun dation model using response data from a run-down, using the inherent unbala nce of the rotor to excite the foundations. The method requires an accurate model of the rotor and an approximate model of the bearings. Of critical i mportance is the quality of the model, which may be defined as the ability of the model to predict the response to unbalance excitations that are diff erent from that present for the identification. It is shown in this paper t hat correct model selection and regularization are vital, to produce a foun dation model that meets this predictability criterion. The method is valida ted using simulated data and also experimental data from a test rig with a 4 m long rotor with four fluid film bearings.