Two-Phase Flow Water Fraction Measurement Using Curvelet Transform and Electrical Capacitance Tomography

ZHANG Haodong; LU Chengcheng; HU Hongli; YANG Haichao; Dong Haijian

doi:10.7652/xjtuxb202407013

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Two-Phase Flow Water Fraction Measurement Using Curvelet Transform and Electrical Capacitance Tomography

更新时间：2025-07-28

- Two-Phase Flow Water Fraction Measurement Using Curvelet Transform and Electrical Capacitance Tomography
- Vol. 58, Issue 7, Pages: 139-147(2024)
- 作者机构：
  
  1. 西安交通大学电力设备电气绝缘国家重点实验室,西安,710049
  2. 西安西电电力电容器有限责任公司,西安,710082
- 作者简介：
- 基金信息：
- DOI：10.7652/xjtuxb202407013
  CLC： TP391.41
- Online First：10 July 2024，
  
  Published：2024
- 稿件说明：
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ZHANG Haodong, LU Chengcheng, HU Hongli, et al. Two-Phase Flow Water Fraction Measurement Using Curvelet Transform and Electrical Capacitance Tomography[J]. 2024, 58(7): 139-147.
DOI：

ZHANG Haodong, LU Chengcheng, HU Hongli, et al. Two-Phase Flow Water Fraction Measurement Using Curvelet Transform and Electrical Capacitance Tomography[J]. 2024, 58(7): 139-147. DOI： 10.7652/xjtuxb202407013.

摘要

针对电容层析成像(ECT)逆问题的欠定性

提出了一种基于曲波变换的图像稀疏重构算法。首先

采用曲波变换基作为稀疏基

从多尺度对模拟介质分布图像进行稀疏表示

提高了ECT灰度值向量的稀疏度; 其次

应用迭代软阈值算法对曲波系数进行稀疏重构

同时使用奇异值分解算法计算最优灵敏度广义逆矩阵; 最后

搭建ECT测量平台

通过静态实验重构5种典型实际流型

验证所提算法的有效性。实验结果表明:所提算法可有效抑制伪影

重构图像边界清晰

同时在图像相关系数、相对图像误差上均优于传统重构算法

比Landweber迭代算法相关系数提高约37.9%

相对误差减小约17.6%; 基于稀疏重构的后处理图像可用于截面含水率的测量

含水率平均误差低于10%

最低为4.32%。该方法有效提高了ECT重构图像质量

能够满足天然气精准开采的工业需求。

Abstract

To address the ill-posed nature of the inverse problem in electrical capacitance tomography(ECT)

this study introduces a sparse reconstruction algorithm based on the curvelet transform. Firstly

the curvelet transform is applied as the sparse basis to decompose binary images of ideal medium distribution across multiple scales and angles. This approach improves the sparsity of ECT grayscale value vectors. Subsequently

the iterative thresholding shrinkage algorithm is employed for the sparse reconstruction of curvelet coefficients

and the optimal sensitivity pseudo-inverse matrix is calculated using the singular value decomposition algorithm. Finally

an ECT measurement platform is established

and five typical real medium phantoms are reconstructed through the static experiment to confirm the effectiveness of the proposed algorithm. Experimental results demonstrate that the algorithm proposed in this paper effectively suppresses artifacts and provides clearly boundaries in reconstructed images. Meanwhile

it outperforms traditional reconstruction algorithms in terms of image correlation coefficient and image relative error. Specifically

compared to the Landweber iteration algorithm

the proposed algorithm shows an increase of approximately 37.9% in image correlation coefficient and a reduction of approximately 17.6% in relative error. Post-processed images can be utilized for water fraction measurement

with an average relative error below 10%

potentially as low as 4.32%. The algorithm introduced in this paper effectively enhances the quality of reconstructed images in ECT

meeting the industrial requirements for precise natural gas extraction.

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