Application of Advanced Parameter Identification Methods for Flight Flutter Data Analysis with Comparisons to Current Techniques,
GRUMMAN AEROSPACE CORP CALVERTON NY
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Grumman has been pursuing the implementation and evaluation of advanced parameter identification software for use in flutter test data processing operations as its Automated Telemetry Station. They have been motivated by aircraft design tending toward thin, lightweight aircraft structures, which make it difficult to use authoritative shaker systems, and the continuing development of high-sped digital computer technology. This development activity is aimed at establishing an on-line processing capability, in the 1985 time frame, that will initially use the maximum likelihood parameter identification algorithm in conjunction with a detailed physical aeroelastic aircraft model to perform optimal flutter test data analysis. Extended Kalman filtering is being considered for eventual use as a second advanced parameter identification method. A mathematical description of the advanced parameter identification approach and Grummans current least-squares flutter analysis procedures are presented. A comparison between this current analysis capability and prototype code for the maximum likelihood parameter identification algorithm on response data excited randomly via atmospheric turbulence and by swept frequency shaker inputs indicates a significant improvement in analysis results with the advanced method.