Embedded Files
The F-16 Ground Vibration Test benchmark features a high order system with clearance and friction nonlinearities at the mounting interface of the payloads.
The experimental data made available to the Workshop participants were acquired on a full-scale F-16 aircraft on the occasion of the Siemens LMS Ground Vibration Testing Master Class, held in September 2014 at the Saffraanberg military basis, Sint-Truiden, Belgium.
During the test campaign, two dummy payloads were mounted at the wing tips to simulate the mass and inertia properties of real devices typically equipping an F-16 in flight. The aircraft structure was instrumented with accelerometers. One shaker was attached underneath the right wing to apply input signals. The dominant source of nonlinearity in the structural dynamics was expected to originate from the mounting interfaces of the two payloads. These interfaces consist of T-shaped connecting elements on the payload side, slid through a rail attached to the wing side. A preliminary investigation showed that the back connection of the right-wing-to-payload interface was the predominant source of nonlinear distortions in the aircraft dynamics, and is therefore the focus of this benchmark study.
A detailed formulation of the identification problem can be found here. All the provided files and information on the F-16 aircraft benchmark system are available for download here. This zip-file contains a detailed system description, the estimation and test data sets, and some pictures of the setup. The data is available in the .csv and .mat file format.
Previously published results on the F-16 Ground Vibration Test benchmark can be found through this link.
Special thanks to Bart Peeters (Siemens Industry Software) for his help in creating this benchmark.
Cite
Cite
Please refer to the F16 benchmark as:
J.P. Noël and M. Schoukens, F-16 aircraft benchmark based on ground vibration test data, 4TU.ResearchData, Dataset, doi: 10.4121/12954911.
Benchmark Results
Benchmark Results
You can submit your own results through this form. Note that the reported results are curated, only complete submissions with meaningful contributions will be included. Candidate entries should make use of the Python dataloader functionalities and figure of merit calculation functions provided through this link.
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