Estimation of single plane unbalance parameters of a rotor-bearing system using Kalman filtering based force estimation technique

This paper proposes a model-based method to estimate single plane unbalance parameters (amplitude and phase angle) in a rotor using Kalman filter and recursive least square based input force estimation technique. Kalman filter based input force estimation technique requires state-space model and response measurements. A modified system equivalent reduction expansion process (SEREP) technique is employed to obtain a reduced-order model of the rotor system so that limited response measurements can be used. The method is demonstrated using numerical simulations on a rotor-disk-bearing system. Results are presented for different measurement sets including displacement, velocity, and rotational response. Effects of measurement noise level, filter parameters (process noise covariance and forgetting factor), and modeling error are also presented and it is observed that the unbalance parameter estimation is robust with respect to measurement noise. •Kalman filter based unbalance parameter estimation technique is proposed.•Unbalance parameters are estimated after unbalance force estimation.•Effects of different measurement sets and noise levels are analyzed.•Unbalance parameter estimation is robust with respect to measurement noise.