Weekly_3-20 - Weekly Progress Report #5 Background Oriented...

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Weekly Progress Report #5 Background Oriented Schlieren AAE 490R/590R 20 March 2008 Hrs. Worked Landon Baur John Tapee
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Progress in Brief – 3/20/08 Week’s Goals 1) Systematically test lined backgrounds for qualitative imaging 2) Evaluate video of moving schlieren object 3) Obtain quantitative pictures of sufficient quality to begin software analysis Week’s Accomplishments 1) A series of lined backgrounds were tested with different camera settings in order to produce a better qualitative image. While we are still not completely satisfied with the quality of images obtained, these images showed marked improvement over the last set of lined background images taken. Also, the deliberate approach taken in sampling different line concentrations and angles provides useful information on which background images produce the best photographs, even if the camera settings are not perfect. 2) As the eye is much more sensitive to movement than small fixed distortions, a video was taken of a candle flame against the same series of lined backgrounds. This was performed somewhat as a sanity check, since we felt we could see the density gradients more with our eye than in the images from the still camera. Thankfully, the video representation mimicked what can be seen with the naked eye much better than the still camera, so we hope to use the video as a baseline representation to which we can compare camera images. 3) In an effort to move forward with this project, a series of pictures were taken using the speckled background for quantitative measurements. Previous images with this background had poor alignment between “no flow” and “with flow” images, so we were very careful to take these images in quick succession with minimal movement of the BOS setup. The result is a series of background-image pairs with no noticeable alignment problems, which should ease the initial BOS analysis. Next Week’s Plan 1) Print random dot backgrounds with uniform dot sizes of only a few camera pixels in diameter 2) Determine algorithm to convert pixel displacements to density gradients a. Purely mathematically b. Using calibration of some sort 3) Study mpiv to extract displacement algorithms
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This note was uploaded on 01/15/2012 for the course AAE 490 taught by Professor Andrisani during the Fall '09 term at Purdue University.

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Weekly_3-20 - Weekly Progress Report #5 Background Oriented...

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