A New Method of Flutter Boundary Prediction for Progressive Variable Speed Based on EM-KS Algorithm

Abstract

The flutter test with progression variable speed is actively explored in recent years. This paper proposes an improved Kalman smoothing filter (EM-KS) algorithm based on expectation maximization for the non-stationary characteristics of the signal in this type of experiment, which can effectively improve the estimation accuracy of time-varying parameter modeling. Combining with the flutter time domain criterion, a new method for flutter boundary prediction of flutter test with progression variable speed that can be recursively implemented is given. Finally, the reliability and engineering applicability of this method are validated by numerical simulation and measured data. The results show that the flutter boundary prediction method based on EM-KS does not depend on the assumption of stationary stochastic process, and the accuracy can meet the actual engineering needs.

Keywords

• em-ks algorithm
• kalman filter smoothing
• tvar
• flutter boundary prediction
• numerical simulation
• flutter time domain criterion