The thesis presents a defocusing technique to extract bubble depth information. Typically, when a bubble is out of focus in an image, the bubble is ignored by applying a filter or thresholding. However, it is known that a bubble image becomes blurred as the bubble moves away from the focal plane. Then, this technique is applied to determine the bubble distance along the optical path based on the blurriness or intensity gradient information of the bubble. Using the image processing algorithm, images captured in three different experiments are analyzed to develop a correlation between the bubble distance and its intensity gradient. The suggested models to predict the bubble depth are also developed based on the measurement data and evaluated with the measured data. When the intensity gradient of the bubble is lower or when a bubble is located farther from the focal plane, the model can predict the distance more accurately. However, the models show larger absolute and relative error when the bubble is near the focal plane. To improve the prediction in that region, another model should be considered. Also, depth of field analysis is introduced in order to compare three experimental results with different imaging setups. The applicability of the approach is analyzed and evaluated. / Master of Science / Gas and liquid measurements of two-phase flow are very challenging, but it has become more important because of many industrial applications such as chemical, petroleum, and energy industries. Many two-phase flow measurement techniques have been developed and utilized for different flow conditions such as fiber optic probe, multi-sensor conductivity probe, wire-mesh sensor, as x-ray densitometry, particle image velocimetry (PIV), and optical imaging. With the development of the technology, the imaging technique can provide better spatial and temporal resolutions as well as image processing speed has improved greatly. In this study, the imaging and defocusing techniques are combined and used to extract bubble depth information. An image processing algorithm has been developed to process bubble images captured by high speed cameras. By measuring the blurriness or intensity gradient information of the bubble, the bubble distance along the optical path is determined. Based on the measurement data, mathematic models are developed to predict the bubble depth. In addition, depth of field analysis is suggested to compare three experimental results with different imaging setups. The applicability of the approach is analyzed and evaluated.
| Identifer | oai:union.ndltd.org:VTETD/oai:vtechworks.lib.vt.edu:10919/78197 |
| Date | January 2017 |
| Creators | Mugikura, Yuki |
| Contributors | Mechanical Engineering, Liu, Yang, Xiao, Heng, Pierson, Mark A. |
| Publisher | Virginia Tech |
| Source Sets | Virginia Tech Theses and Dissertation |
| Language | en_US |
| Detected Language | English |
| Type | Thesis |
| Format | ETD, application/pdf |
| Rights | In Copyright, http://rightsstatements.org/vocab/InC/1.0/ |
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