Time-Frequency Analysis Method Based On Time-Varying Parameter Modeling And Its Applications

Nonstationary signal processing is a branch of modern digital signal processing. Being as an effective tool of nonstationary signal processing, adaptive time-frequency analysis is rapidly developed by using time-varying parameter modeling. How to select time base functions and model is great significance. In this thesis, the theory of time-frequency analysis, especially adaptive time-frequency analysis is considered. New method of adaptive time-frequency analysis is proposed. The characteristics of the method are studied by numerical simulation. The results show that the method is reasonable and feasible.Focused on the features and requirements of flutter test data processing, the method presented here is introduced into flutter boundary prediction based on subcritical turbulence response. By using computer simulation and flutter test of low-speed wind-tunnel of aeroelastical mode, the features of the scheme are investigated. Especially, the technique can be expanded to the flutter test with variable speed.The related software is developed on Labview6.1 for Windows.