Tacholess estimation of time-varying dynamic coefficients of journal bearing based on the square-root cubature Kalman filter

Accurate estimation of time-varying dynamic coefficients (TVDCs) of the journal bearing is important for the dynamic characteristic analysis of rotating machinery. This paper proposes a novel estimation method to identify TVDCs of journal bearings without the tachometers. Firstly, a phase-based method is introduced to extract the instantaneous angular speed (IAS) from the shaft displacement. Secondly, an iteration strategy based on the square-root cubature Kalman filter (SRCKF) is developed to estimate the TVDCs in the time domain. The statespace model and the measured shaft displacements of the journal bearing-rotor system have been applied in the estimation process. The proposed method can estimate TVDCs of journal bearing under speed-variable conditions without a tachometer by combining the phase-based and SRCKF methods. Finally, the simulation and experiments studies are conducted to demonstrate the effectiveness of the proposed methods. The results show that the proposed method can efficiently estimate TVDCs of the journal bearing under speed-variable conditions and at varied measurement noise levels.