PSD replication of a shaking table based on subband adaptive filtering algorithm

To improve the accuracy of power spectral density (PSD) replication of a hydraulic shaking table and to reduce the PSD equalization time, a new system identification (SID) technology based on the subband adaptive filtering algorithm was studied here. The accuracy of SID of the shaking system was one of key factors influencing the PSD replication precision and equalization time through analyzing the principle of PSD equalization of the hydraulic shaking table. The structure of the subband adaptive filtering was investigated, the iteration equation was derived and the convergence conditions of this SID technology were discussed. Meanwhile, a new method for the design of almost full reconstruction cosine modulated filter banks was introduced to decompose a signal into different subbands smoothly and decrease distortions of amplitude and aliasing of the filter banks. Finaly, the efficiency of the subband adaptive filtering SID technology was verified using the simulation of PSD replication of a shaking table with Matlab/Simulink.