Despite the rapid proliferation and increased capabilities of computational fluid diagnostic algorithms, there still exists a need for experimental techniques which can provide global information in an accurate and expeditious manner for augmentation and/or verification of numerical methods. While many optical, non-intrusive techniques such as particle imaging velocimetry have been developed and refined in recent years, systems which can simultaneously extract all three-velocity components are few. We present a technique which utilizes a dual-reference-beam holographic recording and reconstruction system along with a two-step data acquisition and processing method for the determination of in- and out-of-plane velocity components form a single viewing direction. Although still under development, the method, termed holographic diffraction image velocimetry, shows promise to become a useful tool for accurate gross-field diagnostics of complex flows.
A newly conceived technique, termed holographic diffraction image velocimetry, has been investigated computationally and experimentally. The technique can capture 3D three- component velocity fields from a single observation direction. It is based on double-reference- beam double-exposure off axis holography. The independently reconstructed images are then analyzed by applying a cross-correlation technique with transplacing windows. The technique can offer experimental freedom and performance enhancement as compared with conventional techniques in addition to its ability for measuring 3D three-component velocity fields.
In the past, various techniques have been developed for fringe reduction of conventional interferograms. Most typical ones utilize maximum/minimum or side tracking based on conventional image processing. These methods, however, pose a resolution limitation, not allowing acquisition of fractional fringe order numbers. The Fourier Transform method, requiring a relatively large number of fringes or injection of carrier fringes, also has limitations in some applications. The regression method, while simple, confronts a stability problem. That is, the ill-posed nonlinear intensity function cannot provide unique solutions. Here, we present a new approach and some of the test results for the regression method. It is based on iterative independent estimation of the individual terms that appear in the nonlinear model. The test results demonstrate stable convergence and accurate phase extraction by the new regression approach.
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