Wind-tunnel study of the ARMA flutter prediction method

The paper presents an experimental study of flutter prediction via Autoregressive Moving-Average system identification and the use of a linear stability parameter. System identification at subcritical (pre flutter) conditions is based on measured structural responses to excitation by natural air turbulence and is, therefore, attractive for flutter flight testing. The current study investigates the application aspects of the methodology in a dedicated wind tunnel experiment. An elastic wing was designed and manufactured using rapid prototyping, and tested in a subsonic wind tunnel all the way to flutter. Structural responses were recorded by accelerometers, strain gages, and by fiber-optic sensors (measuring strains). The data was processed using signal processing techniques, such as filtering and averaging and used for system identification and flutter prediction. The study focuses on the prediction characteristics and accuracy, method applicability with various dynamic data, and signal processing techniques. The paper addresses practical aspects of the application of the method in a wind-tunnel testing, which are also of significance to flutter flight testing.