Flutter Test Data Processing Based on Improved Hilbert-Huang Transform

Hua Zheng,Junhao Liu,Shiqiang Duan

doi:10.1155/2018/3496870

Hua Zheng, Junhao Liu + Show 1 more

Open Access

https://doi.org/10.1155/2018/3496870

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Abstract

Flutter tests are conducted primarily for the purpose of modal parameter estimation and flutter boundary prediction, the accuracy of which is severely affected by the acquired data quality, structural modal density, and nonstationary conditions. An improved Hilbert-Huang Transform (HHT) algorithm is presented in this paper which mitigates the typical mode mixing effect via modulation. The algorithm is validated by theory, by numerical simulation, and per actual flight flutter test data. The results show that the proposed method could extract the flutter model parameters and predict the flutter speed more accurately, which is feasible for the current flutter test data processing.

Highlights

Flutter tests are conducted primarily for the purpose of modal parameter estimation and flutter boundary prediction, the accuracy of which is severely affected by the acquired data quality, structural modal density, and nonstationary conditions
Many algorithms have been previously developed for identifying flutter test modal parameters, including fast Fourier transform- (FFT-) based methods [4, 5], Random Decrement Technique (RDT) [6], natural excitation technique combined with the eigensystem realization algorithm (NExT-ERA) [7], time series analysis based on the Autoregressive (AR) model [8, 9], and Stochastic Subspace Identification (SSI) [10, 11]
This paper proposes an improved Hilbert-Huang Transform (HHT) which applies to flutter test modal parameter identification

Summary

Introduction

“Flutter” is the self-excited vibration of an elastic structure under the coupling of aerodynamic force, elastic force, and inertial force; it is often accompanied by catastrophic structural damage [1]. Many algorithms have been previously developed for identifying flutter test modal parameters, including fast Fourier transform- (FFT-) based methods [4, 5], Random Decrement Technique (RDT) [6], natural excitation technique combined with the eigensystem realization algorithm (NExT-ERA) [7], time series analysis based on the Autoregressive (AR) model [8, 9], and Stochastic Subspace Identification (SSI) [10, 11] Some of these algorithms are effective, none is ideal; for instance, nonstationary measured data and low signal to noise ratio (SNR) affect the Fourier-based methods. This paper proposes an improved HHT which applies to flutter test modal parameter identification

Hilbert-Huang Transform Theory

Improved HHT and Modal Parameter Identification

Numerical Simulation and Application

Conclusion