Field Identification of Key Dynamic Characteristic Parameters for Rotor-Bearing System Using Kalman Filter

Field identification of the key dynamic characteristic parameters, including the residual unbalance and bearing dynamic coefficients, is of great significance to the dynamic analysis and rotor design of rotating machinery. However, traditional estimation methods are susceptible to routine scattering caused by the ill-posed problem and require external excitation forces, making them inconvenient and costly for engineering applications. Therefore, a novel field estimation method based on the state-space model of the system combined with the Kalman filter method is proposed for the rotor-bearing system without the external excitation force. The principle of this method is designed through an iterative strategy in the time domain, which only requires the steady-state unbalance responses of the two selected locations. Furthermore, simulation studies show that the proposed method can effectively estimate the bearing dynamic coefficients and unbalance parameters under different measurement noise levels. This study provides a comprehensive investigation into the estimation of dynamic characteristics and thereby establishes a reliable foundation for further assessment of the rotor-bearing system's overall performance.