本文選題：數(shù)字全息　切入點：數(shù)字全息粒子追蹤測速　出處：《重慶理工大學(xué)》2017年碩士論文　論文類型：學(xué)位論文

【摘要】：數(shù)字全息技術(shù)是一種利用圖像傳感器記錄物體的振幅和相位信息,并通過計算機模擬光學(xué)的衍射過程而進行物體再現(xiàn)的技術(shù)。數(shù)字全息測量技術(shù)具有無接觸,無損傷等優(yōu)點,可以用于物體的三維形貌、應(yīng)力應(yīng)變場、溫度場、流場等領(lǐng)域的觀測。在一些測量領(lǐng)域,需要實時測量并再現(xiàn)測量目標(biāo)的動態(tài)變化過程并且同時對目標(biāo)場進行三維空間的實時再現(xiàn),數(shù)據(jù)計算量極大,因而必須要加快數(shù)字全息圖處理的速度。本文將基于GPU(Graphics Processing Unit,圖形處理器)的并行計算技術(shù)引入到DHPTV(Digital Holographic Particles Tracing Velocimetry,數(shù)字全息粒子追蹤測速)中,數(shù)字全息圖記錄了粒子的三維空間信息,通過對數(shù)字全息圖進行重建,提取粒子的三維空間坐標(biāo)信息,為了能夠清晰觀測不同深度信息的粒子,需要對整個粒子場以一定的重建間隔進行全場重建,然后通過粒子匹配,可以獲得粒子的三維速度矢量場。由于全場重建的計算量極大,采用了基于GPU的并行計算技術(shù)極大提高了重建速度,實現(xiàn)對空間粒子場的三維速度矢量場的實時重建。為了實現(xiàn)粒子場三維速度矢量場的實時再現(xiàn),本文主要進行了如下研究:(1)數(shù)字全息基本原理以及數(shù)字全息圖重建算法研究;(2)研究了DHPTV的測速原理,提出自己的算法以及計算流程,通過對兩幅旋轉(zhuǎn)粒子的全息圖進行重建測速,對測速結(jié)果進行誤差分析,驗證實驗方法的可行性以及結(jié)果的精度;(3)設(shè)計了一種數(shù)字全息實時顯微鏡,該顯微鏡主要分為硬件系統(tǒng)和軟件系統(tǒng),硬件系統(tǒng)主要是該系統(tǒng)所使用的硬件設(shè)備以及光學(xué)元件,軟件系統(tǒng)主要是基于GPU的并行算法程序。軟件系統(tǒng)的設(shè)計思路是利用Matlab中豐富的API(Application Programming Interface,應(yīng)用程序編程接口)函數(shù)庫建立計算模型,利用CUDA(Compute Unified Device Architecture,統(tǒng)一設(shè)備計算架構(gòu))擴展C++語言對算術(shù)均值濾波,連通域識別、圖像歸一化以及粒子匹配等算法進行編程。為了實現(xiàn)GPU利用率的最大化,使用Kepler架構(gòu)GPU所具有的Hyper-Queue(超工作隊列)特性進行多流編程。對比了Matlab程序運行結(jié)果以及Matlab調(diào)用CUDA程序運行結(jié)果,得到加速比。
[Abstract]:Digital holography is a kind of technology which uses image sensor to record the amplitude and phase information of object and reproduce the object by simulating the diffraction process of optics by computer. The digital holographic measurement technology has the advantages of no contact, no damage and so on. It can be used to observe three-dimensional topography, stress-strain field, temperature field, flow field and so on. It is necessary to measure and reproduce the dynamic change process of the measurement object in real time and reproduce the target field in three dimensional space at the same time. Therefore, we must speed up the processing of digital holograms. In this paper, the parallel computing technology based on GPU(Graphics Processing unit is introduced into DHPTV(Digital Holographic Particles Tracing velocimetric (digital holographic particle tracking velocimetry). The digital hologram records the three-dimensional spatial information of the particle. By reconstructing the digital hologram, the three-dimensional coordinate information of the particle is extracted, so that the particles with different depth information can be clearly observed. It is necessary to reconstruct the whole particle field at a certain interval, and then the three-dimensional velocity vector field of the particle can be obtained by particle matching. The parallel computing technology based on GPU is used to greatly improve the reconstruction speed and realize the real-time reconstruction of the three-dimensional velocity vector field of the space particle field, in order to realize the real-time reconstruction of the three-dimensional velocity vector field of the particle field. In this paper, the basic principles of digital holography and the reconstruction algorithm of digital holograms are studied as follows: the principle of velocity measurement of DHPTV is studied, and its own algorithm and calculation flow are put forward. A digital holographic real time microscope is designed by reconstructing the hologram of two rotating particles and analyzing the error of the velocity measurement results to verify the feasibility of the experimental method and the accuracy of the results. The microscope is mainly divided into hardware system and software system, the hardware system is mainly used in the system of hardware equipment and optical components, The software system is mainly a parallel algorithm program based on GPU. The design idea of the software system is to make use of the rich API(Application Programming interface (application programming interface) function library in Matlab to build the calculation model. Using CUDA(Compute Unified Device Architecture, the extended C language is used to program arithmetic mean filtering, connected domain recognition, image normalization and particle matching. By using Hyper-Queue (Hyper-Queue) feature of Kepler architecture GPU for multi-stream programming, the speedup ratio is obtained by comparing the running results of Matlab programs and the results of Matlab calling CUDA programs.
【學(xué)位授予單位】：重慶理工大學(xué)
【學(xué)位級別】：碩士
【學(xué)位授予年份】：2017
【分類號】：TP391.41;O438.1

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