A new multichannel spectral approach for system identification

The authors consider the estimation of the transfer function associated with periodic systems, such as rotating machine, which involve random processes having infinite as well as finite energy. They propose novel complementary spectral-based approaches for system identification which anticipate this mixture of processes. An example of a two input/single output system identification is presented to illustrate the utility of extension of the single channel mixed spectrum identification technique. It is demonstrated that in mixed spectrum settings the mixed spectrum identification procedure considered can perform significantly better than fast Fourier transform (FFT) and autoregressive (AR) methods for system identification including both magnitude and phase. Moreover, it is robust with respect to the amount of available data