Uncertainty bounds on modal parameters obtained from stochastic subspace identification

The modal parameters of a structure that are estimated from ambient vibration measurements are always subject to bias and variance errors. In this paper, it is discussed how part of the bias errors can be removed and how the variance errors can be estimated from a single ambient vibration test. The bias removal procedure makes use of a stabilization diagram. The variance estimation procedure uses the first-order sensitivity of the modal parameter estimates to perturbations of the measured output-only data. This methodology, that is generally applicable, is illustrated here for the reference-based covariance-driven stochastic subspace identification algorithm. Both simulated and measured vibration data are used to demonstrate the accuracy and practicability of the derived expressions.