Three-dimensional particle field and velocity field reconstruction method based on GPU acceleration

Abstract

The invention relates to a three-dimensional particle field and velocity field reconstruction method based on GPU acceleration, and the method comprises the following steps: obtaining two groups of multi-camera image data with a certain time interval, and a weight matrix search curve of each camera; adopting a GPU, carrying out three-dimensional particle field tomography reconstruction based on the multi-camera image data and the weight matrix search curve, obtaining a reconstructed three-dimensional particle field, and in the tomography reconstruction process, calculating light intensity reconstruction of all voxels in parallel with the number of threads equal to the number of the voxels; and partitioning the reconstructed three-dimensional particle field, extracting data of two diagnosis windows of each data block, performing three-dimensional cross-correlation calculation by adopting a GPU concurrent process to obtain an average speed of all windows, and reconstructing to obtain a three-dimensional speed field. Compared with the prior art, the method has the advantages of effectively reducing calculation time overhead, improving efficiency and the like.

Description

Technical field [0001] The present invention relates to the field of particle image measurement technology, and more particularly to a three-dimensional particle field and speed field reconstruction method based on GPU acceleration. Background technique [0002] Particle Image VelocimeTry (PIV) technology is a non-contactless interference space flow field quantitative measurement means. The PIV technology utilizes the movement of the uniformized minute particle diameter tracking particles follow the fluid, and the motion of the tracer particles is recorded by continuous "light" and "photo" manner, and the motion of particles is extracted from the continuous tracer particle image based on the image processing algorithm. Information, the approximation of fluid spatial motion speed is obtained. TomographicParticle Image VelocimeTry, Tomo-PIV) technology combines PIV technology and computer tomography, CTs, using multi-angle (at least three cameras) and records illuminated particles ...

AI Technical Summary

Problems solved by technology

But since these algorithms run on the CPU, the efficiency improvement is not obvious

In the velocity field reconstruction of PIV technology, scholars at home and abroad have begun to use GPU (Graphics Processing Unit, image processor) to accelerate the cross-correlation algorithm of traditional 2D PIV or 3D PIV to reconstruct the velocity field; but these studies have not gone deeper The optimized GPU thread design only relies on the CUFFT module in the GPU function library to replace the fast Fourier transform in the cross-correlation algorithm. There is no in-depth research on the multi-thread concurrency mode, and the velocity field reconstruction module cannot make full use of the advantages of the GPU.

[0006] In short, the efficiency of particle field reconstruction and velocity field reconstruction has seriously hindered the large-scale application of Tomo-PIV technology, and the existing technology needs to be improved

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