scholarly journals Particle image velocimetry with optical flow

1998 ◽  
Vol 25 (3) ◽  
pp. 177-189 ◽  
Author(s):  
G. M. Quénot ◽  
J. Pakleza ◽  
T. A. Kowalewski
Keyword(s):  
Particle Image Velocimetry ◽  
Optical Flow ◽  
Particle Image ◽  
Image Velocimetry

scholarly journals The Optical Flow Method Research of Particle Image Velocimetry

2015 ◽  
Vol 99 ◽  
pp. 918-924 ◽  
Author(s):  
Wang Hongwei ◽  
Huang Zhan ◽  
Gong Jian ◽  
Xiong Hongliang
Keyword(s):  
Particle Image Velocimetry ◽  
Optical Flow ◽  
Particle Image ◽  
Flow Method ◽  
Optical Flow Method ◽  
Image Velocimetry

Hybrid Optical-Flow-Cross-Correlation Method for Particle Image Velocimetry

2020 ◽  
Vol 142 (5) ◽  
Author(s):  
Tianshu Liu ◽  
David M. Salazar ◽  
Hassan Fagehi ◽  
Hassan Ghazwani ◽  
Javier Montefort ◽  
...  
Keyword(s):  
Particle Image Velocimetry ◽  
Optical Flow ◽  
Hybrid Method ◽  
Cross Correlation ◽  
Particle Image ◽  
Intensity Change ◽  
Flow Method ◽  
Optical Flow Method ◽  
Air Jet ◽  
Image Velocimetry

Abstract A hybrid method for particle image velocimetry (PIV) is developed to overcome the limitations of the optical flow method applied to PIV images with large displacements. The main elements of the hybrid method include a cross-correlation scheme for initial estimation, a shifting scheme for generating a shifted image, and an optical flow scheme for obtaining a refined high-resolution velocity field. In addition, a preprocessing scheme is used for correcting the illumination intensity change. The accuracy of the hybrid method is evaluated through simulations in a parametric space in comparison with the typical correlation methods and optical flow method. Further quantitative comparisons are made in PIV measurements in a circular air jet.

APPLYING FEATURE TRACKING TO PARTICLE IMAGE VELOCIMETRY

2003 ◽  
Vol 17 (04) ◽  
pp. 487-504 ◽  
Author(s):  
DMITRY CHETVERIKOV
Keyword(s):  
Particle Image Velocimetry ◽  
Optical Flow ◽  
Feature Tracking ◽  
Particle Image ◽  
Good Alternative ◽  
Flow Estimation ◽  
Tracking Algorithms ◽  
Alternative Approach ◽  
Image Velocimetry ◽  
Correlation Techniques

Particle Image Velocimetry (PIV) is a popular approach to flow visualization and measurement in hydro- and aerodynamic studies and applications. The fluid is seeded with particles that follow the flow and make it visible. Traditionally, correlation techniques have been used to estimate the displacements of the particles in a digital PIV sequence. These techniques are relatively time-consuming and noise-sensitive. Recently, an optical flow estimation technique developed in machine vision has been successfully used in Particle Image Velocimetry. Feature tracking is an alternative approach to motion estimation, whose application to PIV is proposed and studied in this paper. Two efficient feature tracking algorithms are customized and applied to PIV. The algorithmic solutions of the application are described. In particular, techniques for coherence filtering and interpolation of a velocity field are developed. To assess the proposed and the previous approaches, velocity fields obtained by the different methods are quantitatively compared for numerous synthetic and real PIV sequences. It is concluded that the tracking algorithms offer Particle Image Velocimetry a good alternative to both correlation and optical flow techniques.

Optical flow of non-integer order in particle image velocimetry techniques

2019 ◽  
Vol 155 ◽  
pp. 317-322
Author(s):  
Rafael.G. González-Acuña ◽  
A. Dávila ◽  
Julio C. Gutiérrez-Vega
Keyword(s):  
Particle Image Velocimetry ◽  
Optical Flow ◽  
Particle Image ◽  
Integer Order ◽  
Image Velocimetry

scholarly journals Feasibility of Optical Flow Field Measurements of the Coolant in a Grinding Machine

2021 ◽  
Vol 11 (24) ◽  
pp. 11615
Author(s):  
Björn Espenhahn ◽  
Lukas Schumski ◽  
Christoph Vanselow ◽  
Dirk Stöbener ◽  
Daniel Meyer ◽  
...  
Keyword(s):  
Particle Image Velocimetry ◽  
Fluid Flow ◽  
Flow Field ◽  
Optical Flow ◽  
Particle Image ◽  
Field Measurements ◽  
Optical Flow Field ◽  
Metalworking Fluid ◽  
Image Velocimetry ◽  
Grinding Machine

For industrial grinding processes, the workpiece cooling by metalworking fluids, which strongly influences the workpiece surface layer quality, is not yet fully understood. This leads to high efforts for the empirical determination of suitable cooling parameters, increasing the part manufacturing costs. To close the knowledge gap, a measurement method for the metalworking fluid flow field near the grinding wheel is desired. However, the varying curved surfaces of the liquid phase result in unpredictable light deflections and reflections, which impede optical flow measurements. In order to investigate the yet unknown optical measurement capabilities achievable under these conditions, shadowgraphy in combination with a pattern correlation technique and particle image velocimetry (PIV) are applied in a grinding machine. The results show that particle image velocimetry enables flow field measurements inside the laminar metalworking fluid jet, whereby the shadowgraph imaging velocimetry complements these measurements since it is in particular suitable for regions with spray-like flow regimes. As a conclusion, optical flow field measurements of the metalworking fluid flow in a running grinding machine are shown to be feasible.

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