Repairing Occluded Data for a Mach 0.6 Jet via Data Fusion
| Autor: | Mark Glauser, John F. Dannenhoffer, Christopher J. Ruscher |
|---|---|
| Rok vydání: | 2017 |
| Předmět: |
Physics
Jet (fluid) Image fusion business.industry Acoustics Aerospace Engineering Missing data Sensor fusion 01 natural sciences Pressure sensor 010305 fluids & plasmas Physics::Fluid Dynamics 010309 optics symbols.namesake Optics Particle image velocimetry Mach number Particle tracking velocimetry Computer Science::Computer Vision and Pattern Recognition 0103 physical sciences symbols business |
| Zdroj: | AIAA Journal. 55:255-264 |
| ISSN: | 1533-385X 0001-1452 |
| Popis: | Particle image velocimetry and near-field pressure were collected for an axisymmetric, Mach 0.6 jet. Some of the pressure sensors were in between the laser sheet and camera, causing occlusions in the particle image velocimetry data. Using ideas from the data fusion community, these occluded regions could be repaired. In this case, the particle image velocimetry data could be fused with the knowledge that the velocity field was symmetric about the center axis using a new technique called fused proper orthogonal decomposition, which is inspired by gappy proper orthogonal decomposition and image/wavelet fusion. Using this technique, 90% of the missing data could be estimated with 10% error. |
| Databáze: | OpenAIRE |
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