Uncertainty Estimation in Experimental Whirl Flutter Modes Identification

This paper deals with the uncertainty estimation of identified frequency and damping trends of whirl flutter modes, obtained by applying system identification methods on experimental data. In particular, two different identification approaches are considered, namely the free-decay analysis by using Matrix Pencil algorithm and the Data-Driven Stochastic Subspace Identification method (SSI), applied to system response to stochastic input. The two approaches lead to as many uncertainty estimation methodologies, both leveraging the bootstrapping statistical process. A full validation procedure is then set up to assess the accuracy of such methods in correctly quantifying the uncertainty of the estimated statistics. To do so, a wing-rotor state-space linear numerical model is used to simulate system response to both dwell and stochastic inputs. The state space numerical system aims to replicate the ATTILA wing-rotor wind-tunnel model, which falls in the framework of Clean Sky 2 European program to investigate the possible occurrence of whirl-flutter instability in tiltrotor configurations. Hence, one of the proposed methodologies is applied to ATTILA experimental data for both modal identification and uncertainty estimation, and the processed flutter trends are reported in a few conditions of particular interest due to the progressive approaching of whirl-flutter condition.