提出一种电学层析成像(ECT)图像重建优化算法。通过将传统正则化算法转化为最小二乘问题进行求解,结合lp范数逼近正则化最小化问题,利用重新加权的方法进行迭代计算。以油-气两相流模型进行仿真及静态实验,将所提出的优化算法与常用的LBP、Landweber迭代及Tikhonov正则化算法进行对比。结果表明,与常用算法相比,采用该优化算法对管道中心物体及多物体分布流型进行图像重建,其图像相对误差均为最低,且重建图像的形状保真度明显提高。
Abstract
An image reconstruction algorithm based on optimization algorithm for electrical capacitance tomography (ECT) is proposed. In order to approximate the regularization minimization problem, the traditional regularization algorithm is transformed into the least squares problem by the lp-norm, and the iterative calculation is performed by the re-weighting method. Simulation experiment and static experiment is carried out for oil-gas two-phase flow model. The presented optimization reconstruction algorithm is compared with the commonly used LBP, Landweber iteration and Tikhonov regularization algorithm. The results show that lower image relative error and obviously improved shape fidelity of the reconstructed images can be obtained using the presented algorithm for the flow patterns which contain the object in the center of the pipe or many objects in the pipe.
关键词
计量学;电容层析成像 /
油-气两相流;图像重建;优化算法;正则化
Key words
metrology /
electrical capacitance tomography /
oil-gas two-phase flow /
image reconstruction /
optimization algorithm /
regularization
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参考文献
［1］赵玉磊, 郭宝龙, 闫允一. 电容层析成像技术的研究进展与分析［J］. 仪器仪表学报, 2012, 33 (8): 1909-1920.
Zhao Y L, Guo B L, Yan Y Y. Latest development and analysis of electrical capacitance tomography technology［J］. Chinese Journal of Scientific Instrument, 2012, 33 (8): 1909-1920.
［2］张立峰, 刘昭麟, 田沛. 基于压缩感知的电容层析成像图像重建算法［J］. 电子学报, 2017, 45 (2): 353-358.
Zhang L F, Liu Z L, Tian P. Image reconstruction algorithm for electrical capacitance tomography based on compressed sensing［J］. Chinese Journal of Electronics, 2017, 45 (2): 353-358.
［3］张立峰, 朱炎峰. 电容层析成像系统阵列电极三维优化设计［J］. 计量学报, 2020, 41 (8): 947-952.
Zhang L F, Zhu Y F. Three-dimensional Optimal Design of Array Electrode for Electrical Capacitance Tomography System［J］. Acta Metrologicala Sinica, 2020, 41 (8): 947-952.
［4］李斯斯. 图像融合算法的应用研究［D］. 保定:华北电力大学, 2017.
［5］刘晶. 基于COMSOL的电容层析成像激励测量模式研究［D］. 保定:华北电力大学, 2016.
［6］赵愉, 岳士弘, 张洋洋, 等. 航空发动机中气液两相流的可视化检测［J］. 北京航空航天大学学报, 2017, 43 (11): 2345-2351.
Zhao Y, Yue S H, Zhang Y Y, et al. Visual Detection of Gas-Liquid Two-Phase Flow in Aeroengine［J］. Journal of Beijing University of Aeronautics and Astronautics, 2017, 43 (11): 2345-2351.
［7］张立峰. 压缩感知在电容层析成像中的应用［J］. 北京航空航天大学学报, 2017, 43 (11): 2316-2321.
Zhang L F. Application of Compressed Sensing in Electr-ical Capacitance Tomography［J］. Journal of Beijing University of Aeronautics and Astronautics, 2017, 43 (11): 2316-2321.
［8］张立峰, 蒋玉虎. 电容层析成像三维图像重建研究［J］. 计量学报, 2019, 40 (3): 462-465.
Zhang L F, Jiang Y H. Study on 3D Image Recons-truction of Electrical Capacitance Tomography［J］. Acta Metrologica Sinica, 2019, 40 (3): 462-465.
［9］吴新杰, 闫诗雨, 徐攀峰, 等. 基于稀疏度自适应压缩感知的电容层析成像图像重建算法［J］. 电子与信息学报, 2018, 40 (5): 1250-1257.
Wu X J, Yan S Y, Xu P F, et al. An Image Recons-truction Algorithm for Electrical Capacitance Tomography Based on Sparse Adaptive Compressive Sensing［J］. Journal of Electronics & Information Technology, 2018, 40 (5): 1250-1257.
［10］温丽梅, 周苗苗, 李明, 等. 改进的Tikhonov正则化图像重建算法［J］. 计量学报, 2018, 39 (5): 679-683.
Wen L M, Zhou M M, Li M, et al. Improved Tikhonov regularization image reconstruction algorithm［J］. Acta Metrologicala Sinica, 2018, 39 (5): 679-683.
［11］Nie F P, Wang X Q, Huang H. Clustering and project-ed clustering with adaptive neighbors［C］// Acm Sigkdd International Conference on Knowledge Discovery & Data Mining. ACM, 2014.
［12］Shi X S, Nie F P, Lai Z H, et al. Robust Principal Component Analysis via Optimal Mean by Joint l2, 1 and Schatten p-norms minimization［J］. Neurocomputing, 2018, 283 (3): 205-213.
［13］Nie F P, Wang H, Huang H, et al. Joint Schatten p-norm and lp-norm robust matrix comletion for missing value recovery［J］. Knowledge and Information Systems, 2015, 42 (3): 525-544.
［14］肖理庆, 王化祥, 邵晓根. ERT新型拓扑结构有限元模型优化［J］. 仪器仪表学报, 2014, 35 (6): 1298-1305.
Xiao L Q, Wang H X, Shao X G. Optimization of ERT new topological structure finite element model［J］. Chinese Journal of Scientific Instrument, 2014, 35 (6): 1298-1305.
基金
国家自然科学基金(61973115);中央高校基本科研业务费资助(2017MS131)
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