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Data Analytics in Wind Tunnel Measurements

3/20/2018

 
PhD candidate Aaron Defreitas is leading a test in the Virginia Tech Stability Wind Tunnel investigating data analysis methods for large diverse sensor systems. His analysis procedures are being used to identify anomalous results in real-time while collecting high volume data. The figure below shows the automated detection of a bad pressure port in a total pressure rake measuring the wake profile downstream of an airfoil. This port is seen in the profile at -10 degrees AoA. This is an obvious error, but the method is proving useful in detecting very small anomalies as well. These methods should improve identification of smaller errors that may be overlooked by a user trying to manage the collection of high volume data manually.
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Picture
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Covariance matrix of pressure coefficient in wake of airfoil

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