Genetic algorithm based fast X-ray computed tomographic method for multiphase flow measurement (Ⅱ)Validation by real experiments

丁宇龙 吴昌宁 程易 金涌

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Genetic algorithm based fast X-ray computed tomographic method for multiphase flow measurement (Ⅱ)Validation by real experiments

更新时间：2025-12-10

- Genetic algorithm based fast X-ray computed tomographic method for multiphase flow measurement (Ⅱ)Validation by real experiments
- CIESC Journal Issue 2, (2007)
- 作者机构：
  
  清华大学化工系
- 作者简介：
- 基金信息：
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- Online First：05 February 2007，
  
  Published：05 February 2007
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丁宇龙吴昌宁程易金涌. Genetic algorithm based fast X-ray computed tomographic method for multiphase flow measurement (Ⅱ)Validation by real experiments[J]. CIESC Journal, 2007, (2).
DOI：

丁宇龙吴昌宁程易金涌. Genetic algorithm based fast X-ray computed tomographic method for multiphase flow measurement (Ⅱ)Validation by real experiments[J]. CIESC Journal, 2007, (2). DOI：

摘要

采用静态实验模型和一套X射线测试系统模拟了二值多相体系多角度同时投影的X射线CT测量过程。静态实验模型模拟空气-水两相体系，截面相浓度分布满足0-1特征。X射线测试系统由一台工作电压为150 kV的闪光X射线机、一台X射线平板检测器和一套数据采集单元组成。通过旋转静态实验模型，分步实现不同角度的投影数据采集。基于模拟的多角度“同时”采集的投影数据，使用本系列研究所构建的基于遗传算法的快速X射线CT多相流测试技术（GA-XCT）对截面图像进行重建，测试结果表明：在3～24个有限角度实测投影数据的情况下，GA-XCT表现出了明显优于传统CT图像重构算法（滤波反投影算法）的图像重构能力，且具有良好的抗噪声能力。

Abstract

Simultaneous measurements of X-ray projection data from several angles around a static experimental model were implemented by rotating the model between an X-ray tube and a flat plate detectorThe static model simulated a two-phase system with water and air inside

forming four bubbles at the cross-sectionThe measurement system consisted of a Model 150-I Mobile X-ray Unit operated at the potential of 150 kV

a MiniX-1 X-ray flat plate detector

and a data acquisition systemBy using the measured instantaneous projection data from different angles

the cross-sectional image was reconstructed with the established genetic algorithm based fast X-ray computed tomographic method(GA-XCT)A series of real experiments clearly demonstrated the feasibility and capability of the GA-XCT in the application of “bubbles” reconstruction compared with the conventional CT reconstruction algorithm using limited projection dataMeanwhile

the GA based image reconstruction is robust to the noise.

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