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

一种基于EM-KS算法的连续变速颤振边界预测方法

¹ School of Power and Energy, Northwestern Polytechnical University, Xi'an 710072, China
² Shanghai Aircraft Design and Reseavch Institute, Shanghai 201210, China

Received: 8 November 2018

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.

摘要

连续变速颤振试验（FTPVS）是近年来积极探索的一种颤振试验方案。针对该类试验中信号非平稳的特点，创新性地将期望最大化方法迭代优化的思想用于改善连续变速颤振信号的建模精度，提出了一种基于该方法的卡尔曼滤波平滑（EM-KS）算法，有效提高了时变参数的辨识性能。进而结合颤振时域判据，给出了可递推实现的连续变速颤振试验的颤振边界预测方法。最后通过数值仿真和实测数据对所提方法的可靠性与工程适用性进行了验证，结果表明，基于EM-KS颤振边界预测方法不依赖于平稳随机过程的假设，精确度可以满足实际工程需要。