Dynamic Behavior Analysis of Touchdown Process in Active Magnetic Bearing System Based on Kalman Filtering

Abstract

Magnetic bearings are widely applied in High Temperature Gas-cooled Reactor (HTGR) and auxiliary bearings are important backup and safety components in AMB systems. The dynamic analysis of the AMB rotors touchdown process is an important foundation for designing auxiliary bearings. In this paper, a data-based dynamic analysis of the touchdown process is proposed. The dynamic model of the touchdown process is firstly established and then the nonlinear extended Kalman filtering technique is applied. Based on the dynamic model and Kalman filtering technique, the proposed method can offer estimations of rotor’s displacements, velocities and accelerations from noisy observations. The proposed method is validated by the experiment data from touchdown experiments. The touchdown experiments are performed on an experimental system with a 440kg heavy rotor, the rotational speed in the experiments is 5000RPM and no brake is applied.

Dynamic Behavior Analysis of Touchdown Process in Active Magnetic Bearing System Based on a Machine Learning Method

“…The data in the experiments are attained from 21 touchdown experiments on the backup helium circulator system of HTR-10. A detailed description of this system can be found in [11,13,33]. These experiments are performed with various conditions; for example, the brake of drive motor will be applied and an additional axial load (about 2000 N) will be applied by an axial loader [29].…”

“…In [13], these parameters are regarded as constants and these values are determined theoretically or empirically. However, in this paper, these parameters are modeled as functions of auxiliary bearing deformation and rotor velocity.…”

“…More specifically, this paper is an extension of [13] and the dynamical model proposed in [13] is utilized. In [13], some mechanical parameters, such as stiffness, damping ration, and friction coefficient, are introduced and regarded as known constants.…”

“…However, this work did not consider the friction between the rotor and auxiliary bearing. Sun et al [13] estimated the displacements, velocities, and accelerations of the rotor during touchdown from both the dynamic model and noisy data, the dynamic model of the rotor is introduced, and Kalman filtering technique is applied. Most papers in this region emphasize the dynamic behavior of the rotor touchdown process and the influence of different factors such as the air gap, rotational speed, and the eccentricity.…”

“…In [13], some mechanical parameters, such as stiffness, damping ration, and friction coefficient, are introduced and regarded as known constants. In this paper, however, these parameters are modeled as functions of deformation of auxiliary bearing and velocity of the rotor.…”