CONFERENCE PROCEEDINGS
Advanced Search
Home > Proceedings > Volume 11379 > Article
Paper
23 April 2020 Flutter boundary prediction under continuous variable speed based on time series models
Hao Bai, Li Zhou
Author Affiliations +
Proceedings Volume 11379, Sensors and Smart Structures Technologies for Civil, Mechanical, and Aerospace Systems 2020; 1137923 (2020) https://doi.org/10.1117/12.2558038
Event: SPIE Smart Structures + Nondestructive Evaluation, 2020, Online Only
Abstract
Based on the time series model, the modal parameters of the continuous variable flutter test response signal are identified, and a set of flutter boundary prediction methods suitable for turbulent excitation is developed in this paper. In order to ensure the accuracy of the method, a modal parameter identification method is used to analyze the traditional autoregressive model (AR) and the time-varying autoregressive model (TVAR), and compare the accuracy of the two models. Finally, the method is applied to the flutter boundary prediction of turbulence signals. The prediction method combines the time series model with the stability criterion, constructs the stability parameters of the response signal, and the prediction results of flutter critical velocity are obtained by fitting and extrapolation. The numerical example shows the analysis results of the two models and proves the feasibility and effectiveness of the method. Finally, this method is used to predict the flutter boundary of low-speed wind tunnel test data, and the prediction error is less than 5%.
© (2020) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Citation Download Citation
Hao Bai and Li Zhou "Flutter boundary prediction under continuous variable speed based on time series models", Proc. SPIE 11379, Sensors and Smart Structures Technologies for Civil, Mechanical, and Aerospace Systems 2020, 1137923 (23 April 2020); https://doi.org/10.1117/12.2558038
ACCESS THE FULL ARTICLE
ORGANIZATIONAL
Sign in with credentials provided by your organization.
INSTITUTIONAL
Select your institution to access the SPIE Digital Library.
SELECT YOUR INSTITUTION
PERSONAL
Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.
PERSONAL SIGN IN
No SPIE Account? Create one
PURCHASE THIS CONTENT
SUBSCRIBE TO DIGITAL LIBRARY
50 downloads per 1-year subscription
Members: $195
Non-members: $335 ADD TO CART
25 downloads per 1 - year subscription
Members: $145
Non-members: $250 ADD TO CART
PURCHASE SINGLE ARTICLE
Includes PDF, HTML & Video, when available
Members: $17.00
Non-members: $21.00 ADD TO CART
PROCEEDINGS
 12 PAGES
DOWNLOAD PAPER SAVE TO MY LIBRARY
GET CITATION
Advertisement
Advertisement
RIGHTS & PERMISSIONS
Get copyright permission  Get copyright permission on Copyright Marketplace
KEYWORDS
Autoregressive models
Data modeling
Signal processing
Systems modeling
Wind measurement
Analytical research
RELATED CONTENT
Subscribe to Digital Library
Receive Erratum Email Alert
Back to Top