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      • HARVEST
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      Uncertainty analysis of a particle tracking algorithm developed for super-resolution particle image velocimetry

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      UncertaintyAnalysisOfaParticleTrackingAlgorithmDevelopedforSuperResolutionParticleImageVelocimetry.pdf (1.191Mb)
      Date
      2003-05-26
      Author
      Joseph, Sujith
      Type
      Thesis
      Degree Level
      Masters
      Metadata
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      Abstract
      Particle Image Velocimetry (PIV) is a powerful technique to measure the velocity at many points in a flow simultaneously by performing correlation analysis on images of particles being transported by the flow. These images are acquired by illuminating the flow with two light pulses so that each particle appears once on each image. The spatial resolution is an important parameter of this measuring system since it determines its ability to resolve features of interest in the flow. The super-resolution technique maximises the spatial resolution by augmenting the PIV analysis with a second pass that identifies specific particles and measures the distance between them. The accuracy of the procedure depends on both the success with which the proper pairings are identified and the accuracy with which their centre-to-centre distance can be measured. This study presents an analysis of both the systematic uncertainty and random uncertainty associated with this process. The uncertainty is analysed as a function of several key parameters that define the quality of the image. The uncertainty analysis is performed by preparing 4000 member ensembles of simulated images with specific setpoints of each parameter. It is shown that the systematic uncertainty is negligible compared to the random uncertainty for all conditions tested. Also, the image contrast and the selection of a threshold for the particle search are the most critical parameters influencing both success rate and uncertainty. It is also shown that high image intensities still yield accurate results. The search radius used by the super-resolution algorithm is shown to be a critical parameter also. By increasing the search radius, the success rate can be increased although this is accompanied by an increase in random uncertainty.
      Degree
      Master of Science (M.Sc.)
      Department
      Mechanical Engineering
      Program
      Mechanical Engineering
      Supervisor
      Bugg, James D.
      Committee
      Habibi, Saeid R.; Evitts, Richard W.; Burton, Richard T.; Sumner, David
      Copyright Date
      May 2003
      URI
      http://hdl.handle.net/10388/etd-08042003-064037
      Subject
      High Resolution PIV. Simulated PIV images.
      LDV
      whole field velocity measurements
      Error Measurements in PIV
      Uncertainty analysis of PIV algorithm
      Super-resolution particle image velocimetry
      PIV
      SPIV
      hot-wire measurements
      Particle Image Velocimetry
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