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
: 2024-03-09。作者简介: 张皓冬(1999—),男,硕士生
胡红利(通信作者),男,教授,博士生导师。基金项目: 国家自然科学基金资助项目(52177009)
网络首发:2024-07-10,
纸质出版:2024
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张皓冬, 陆程程, 胡红利, 等. 采用曲波变换和电容层析成像的两相流含水率测量方法[J]. 西安交通大学学报, 2024,58(7):139-147.
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.
张皓冬, 陆程程, 胡红利, 等. 采用曲波变换和电容层析成像的两相流含水率测量方法[J]. 西安交通大学学报, 2024,58(7):139-147. DOI: 10.7652/xjtuxb202407013.
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.
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。
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.
马跃. 油水两相电容层析成像流型辨识方法研究 [D]. 大庆: 东北石油大学, 2020.
梁士国. 气液两相流电容层析成像研究 [D]. 北京: 中国科学院工程热物理研究所, 2018.
THORN R, JOHANSEN G A, HJERTAKER B T. Three-phase flow measurement in the petroleum industry [J]. Measurement Science and Technology, 2013, 24(1): 012003.
PENG Lihui, YE Jiamin, LU Geng, et al. Evaluation of effect of number of electrodes in ECT sensors on image quality [J]. IEEE Sensors Journal, 2012, 12(5): 1554-1565.
ZEESHAN Z, ZUCCARELLI C E, OSPINA ACERO D, et al. Enhancing resolution of electrical capacitive sensors for multiphase flows by fine-stepped electronic scanning of synthetic electrodes [J]. IEEE Transactions on Instrumentation and Measurement, 2019, 68(2): 462-473.
李海青, 黄志尧. 特种检测技术及应用 [M]. 杭州: 浙江大学出版社, 2000.
王胜南, 李敏艳. 基于ECT的气固两相流颗粒浓度在线无损检测 [J]. 电子测量与仪器学报, 2021, 35(12): 52-58.
WANG Shengnan, LI Minyan. On-line nondestructive particle concentration measurement of gas-solid two-phase flow based on ECT [J]. Journal of Electronic Measurement and Instrumentation, 2021, 35(12): 52-58.
杨海潮, 胡红利, 陆程程, 等. 采用多任务学习和电容层析成像的两相流参数测量方法 [J]. 西安交通大学学报, 2023, 57(3): 202-211.
YANG Haichao, HU Hongli, LU Chengcheng, et al. Two-phase flow parameter measurement using multi-task learning and electrical capacitance tomography [J]. Journal of Xi'an Jiaotong University, 2023, 57(3): 202-211.
范优飞, 胡红利, 杨帆, 等. 一种48电极可配置电容层析成像系统模型 [J]. 西安交通大学学报, 2015, 49(4): 110-115.
FAN Youfei, HU Hongli, YANG Fan, et al. A model of electrical capacitance tomography system with configurable 48 electrodes [J]. Journal of Xi'an Jiaotong University, 2015, 49(4): 110-115.
YANG Wuqiang. Key issues in designing capacitance tomography sensors [C]//Sensors, 2006 IEEE. Piscataway, NJ, USA: IEEE, 2006: 497-505.
YANG Wuqiang. Design of electrical capacitance tomography sensors [J]. Measurement Science and Technology, 2010, 21(4): 042001.
YANG Yunjie, PENG Lihui. A configurable electrical capacitance tomography system using a combining electrode strategy [J]. Measurement Science and Technology, 2013, 24(7): 074005.
LIU Zhijian, BABOUT L, BANASIAK R, et al. Effectiveness of rotatable sensor to improve image accuracy of ECT system [J]. Flow Measurement and Instrumentation, 2010, 21(3): 219-227.
马敏, 孙美娟, 李明. 基于lp-范数的ECT图像重建算法研究 [J]. 计量学报, 2020, 41(9): 1127-1132.
MA Min, SUN Meijuan, LI Ming. Research on ECT image reconstruction algorithm based on lp-norm [J]. Acta Metrologica Sinica, 2020, 41(9): 1127-1132.
QIN Xuebin, SHEN Yutong, HU Jiachen, et al. Image reconstruction for ECT under compressed sensing framework based on an overcomplete dictionary [J]. Computer Modeling in Engineering Sciences, 2022, 130(3): 1699-1717.
ZHANG Lifeng, SONG Yajie. Application of gradient projection for sparse reconstruction to compressed sensing for image reconstruction of electrical capacitance tomography [J]. Journal of Electrical and Electronic Engineering, 2018, 6(2): 46-52.
WU Xinjie, HUANG Guoxing, WANG Jingwen, et al. Image reconstruction method of electrical capacitance tomography based on compressed sensing principle [J]. Measurement Science and Technology, 2013, 24(7): 075401.
刘昭麟. 基于压缩感知理论的电容层析成像算法研究 [D]. 保定: 华北电力大学, 2017.
YE Jiamin, WANG Haigang, YANG Wuqiang. Image reconstruction for electrical capacitance tomography based on sparse representation [J]. IEEE Transactions on Instrumentation and Measurement, 2015, 64(1): 89-102.
张华, 陈小宏, 李红星, 等. 曲波变换三维地震数据去噪技术 [J]. 石油地球物理勘探, 2017, 52(2): 226-232.
ZHANG Hua, CHEN Xiaohong, LI Hongxing, et al. 3D seismic data de-noising approach based on curvelet transform [J]. Oil Geophysical Prospecting, 2017, 52(2): 226-232.
张杨, 王君恒, 曹炼鹏, 等. 曲波变换在位场信号提取中的应用研究 [J]. 物探与化探, 2021, 45(1): 84-94.
ZHANG Yang, WANG Junheng, CAO Lianpeng, et al. A study of the application of curvelet transform to potential field signal extraction [J]. Geophysical and Geochemical Exploration, 2021, 45(1): 84-94.
XU Xiang, LI Jun, LI Shutao, et al. Curvelet transform domain-based sparse nonnegative matrix factorization for hyperspectral unmixing [J]. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 2020, 13: 4908-4924.
DONOHO D L, CANDES E J. Digital ridgelet transform via digital polar coordinate transform: US 6766062 B1 [P]. 2004-07-20.
唐刚. 基于压缩感知和稀疏表示的地震数据重建与去噪 [D]. 北京: 清华大学, 2010.
唐凯豪. 用于气-水两相流可视化监测的电容层析成像技术关键问题研究 [D]. 西安: 西安交通大学, 2022.
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