Multi-Frequency Periodic Vibration Suppressing With FBLMS Algorithm in Active Magnetic Bearing-Rotor System
In active magnetic bearing (AMB)-rotor system, a method for the multi-frequency periodic vibration suppressing is proposed by an adaptive structure with the finite-duration impulse response (FIR) filter. To cater for the requirement of the long duration impulse response filter arisen in the AMB-rotor system, the Fast Block Least Mean Square (FBLMS) algorithm is adopted to efficiently implement the computation of linear convolution and linear correlation at a computational cost far less than that of the conventional FIR filter of time domain. The unique feature of the FBLMS algorithm is characterized by no influence on the computational complexity, regardless of the number of the vibration frequency components within the range of sampling frequency. The convergence rate of each frequency component can be adjusted by assigning the individual step size parameter for each filter weight. Furthermore, each harmonic component of the vibration can be addressed respectively or together. The experimental results of the reciprocating simulating disturbance test and the rotating harmonic vibration test show that the proposed adaptive structure with the FBLMS algorithm can achieve the good effectiveness for suppressing the multi-frequency periodic vibration.
Booktitle: Proceedings of ISMB12