Comparison of methods for estimating short-term damping of idling wind turbine modes from measurements

Abstract

Three methods for estimating time-varying (Hilbert-Huang transform, continuous wavelet transformation and partial Floquet analysis) and one for time-invariant (stochastic subspace identification) natural frequencies and viscous damping ratios based on free responses are tested and compared. The methods’ performance and sensitivities to several system characteristics are tested with a series of simulated responses. It is shown that, of the group of three methods, partial Floquet is the most suitable and Hilbert-Huang transform is unsuitable for the responses tested. Of the four methods tested, the stochastic subspace identification method is shown to be the method most robust to measurement noise, but its estimates contain notable bias error due to the short time series used. Natural frequencies and damping ratios of four edgewise blade modes are estimated based on measured responses from a single output location. The median of the estimated damping for these four modes have been calculated to be almost the same.