Adaptive Time-Frequency Analysis And It's Application To Signal Processing Of Flutter Test

Time-frequency analysis represents simultaneously the energy or intensity of signal in time and frequency. It's of great significance how to adaptively describe a signal in time-frequency domain. In this thesis, the theory of time-frequency analysis, especially adaptive time-frequency analysis is considered. Two new methods of adaptive time-frequency analysis are proposed based on adaptive signal expansion and adaptive filtering. The characteristics of the two methods are studied by numerical simulation. The results show that both the methods are reasonable and feasible.As a special form of vibration, flutter is a major feature closed with the run environment and safety of aircraft, which is an important project of Human-Machine-Environment Engineering. Focused on the nonstationary features and analysis requirements of flutter test data, the application scheme is brought forward for flutter signal processing. By using computer simulation and flutter test of low-speed wind-tunnel of some aeroelastical modes, the characteristics of the scheme are investigated. Especially, the technique proposed here can be expanded to the flutter test with variable speed.The related software is developed on LabVIEW for Windows.