Kalman filter-based subspace identification for operational modal analysis under unmeasured periodic excitation

The modes of linear time invariant mechanical systems can be estimated from output-only vibration measurements under ambient excitation conditions with subspace-based system identification methods. In the presence additional unmeasured periodic excitation, for example due to rotating machinery, described by a state-space model where input dynamics appear as subsystem in addition structural interest. While subspace is still consistent this case, may render modal parameter estimation difficult, and often disturb close modes. aim work develop method parameters while rejecting influence input. proposed approach, information data non-steady state Kalman filter, then removed original output signal an orthogonal projection. Consequently, are rejected estimates, it shown that consistently estimated. Furthermore, standard analysis procedures, like stabilization diagram, easier interpret. validated on Monte Carlo simulations applied both laboratory full-scale structure operation.