基于深层小波网络的电容层析成像图像重建

doi:10.3969/j.issn.1000-1158.2024.09.13

Abstract
Figure/Table
References (16)
Related Citation (15)

Download: PDF (0 KB) HTML (1 KB)
Export: BibTeX | EndNote (RIS)

Abstract The image reconstruction algorithm of electrical capacitance tomography (ECT) based on deep wavelet network is presented . The Landweber algorithm is used to generate the initial reconstructed image as the input of the network. Taking the U-Net deep convolutional neural network model as the backbone model, the wavelet transform is introduced into the upper and lower sampling layers to extract the features of different levels and the high-frequency feature transfer channel is built through a skip connection to retain more detailed information and make full use of global and local information features in the feature map. Both simulation and experimental results show that the proposed image reconstruction algorithm has higher image reconstruction accuracy. The average relative image errors of simulated and static experimental reconstructed images were 0.1918 and 0.6570, respectively, with average correlation coefficients of 0.9685 and 0.8169.

Key words： multiphase flow measurement electrical capacitance tomography image reconstruction deep learning wavelet transform

Received: 22 September 2023 Published: 26 September 2024

PACS:	TB937
	TB973

	Service

	E-mail this article
	Add to my bookshelf
	Add to citation manager
	E-mail Alert
	RSS
	Articles by authors
	ZHANG Lifeng
	QIAN Lifeng
	HUA Huichun
	LIU Shuai

Cite this article:

ZHANG Lifeng,QIAN Lifeng,HUA Huichun, et al. Image Reconstruction of Electrical Capacitance Tomography Based on Deep Wavelet Networks[J]. Acta Metrologica Sinica, 2024, 45(9): 1353-1359.

URL:

http://jlxb.china-csm.org:81/Jwk_jlxb/EN/10.3969/j.issn.1000-1158.2024.09.13 OR http://jlxb.china-csm.org:81/Jwk_jlxb/EN/Y2024/V45/I9/1353

［5］	张立峰, 戴力. 基于鲁棒正则化极限学习机的电容层析成像图像重建［J］. 计量学报, 2022, 43(8): 1044-1049.
［8］	马敏, 张彩霞, 姬晶晶, 等. 改进的共轭梯度算法的图像重建算法［J］. 计量学报, 2013, 34(1): 27-30.
［15］	张立峰, 张明. 一种电容层析成像图像重建优化算法［J］. 计量学报, 2021, 42(9): 1155-1159.
［1］	YANG W Q, PENG L H. Image Reconstruction Algorithms for Electrical Capacitance Tomography［J］. Measurement Science and Technology, 2002, 14(1): R1-R13.
［2］	LI A, MENG S, HUANG K, et al. On the Concentration Models in Electrical Capacitance Tomography for Gas-fluidized Bed Measurements［J］. Chemical Engineering Journal, 2022, 435: 134989.
［4］	HU D, TIAN Y, CHANG L Y, et al. Estimation of Combustion Temperature Field From The Electrical Admittivity Distribution Obtained by Electrical Tomography［J］. IEEE Transactions on Instrumentation and Measurement, 2020, 69(9): 6271-6280.
［6］	YANG Y, PENG L H. Data Pattern with ECT Sensor and Its Impact on Image Reconstruction［J］. IEEE Sensors Journal, 2013, 13(5): 1582-1593.
［7］	ZHANG L F, WANG H X. A new normalization method based on electrical field lines for electrical capacitance tomography ［J］. Measurement Science and Technology, 2009, 20(10): 104028.
［9］	ZHENG J, MA H, PENG L H. A CNN-based Image Reconstruction for Electrical Capacitance Tomography［C］//2019 IEEE International Conference on Imaging Systems and Techniques. 2019: 1-6.
［10］	TAN C, LU S, DONG F, et al. Image Reconstruction Based on Convolutional Neural Network for Electrical Resistance Tomography［J］. IEEE Sensors Journal, 2019, 19(1): 196-204.
	ZHANG L F, WANG H R. Image Reconstruction of Electrical Capacitance Tomography Based on Convolutional Neural Network and Finite Element Simulation［J］. Journal of System Simulation, 2022, 34 (4): 712-718.
［12］	DEABES W, ABDEL-HAKIM A E, BOUAZZA K E, et al. Adversarial Resolution Enhancement for Electrical Capacitance Tomography Image Reconstruction［J］. Sensors, 2022, 22(9): 3142.
	ZHANG L F, DAI L. Image reconstruction of electrical capacitance tomography based on robust regularization limit learning machine ［J］. Acta Metrologica Sinica, 2022, 43 (8): 1044-1049.
［13］	李峰, 谭超, 董峰. 全连接深度网络的电学层析成像算法［J］. 工程热物理学报, 2019, 40(7): 1526-1531.
［14］	ZUO B, CHENG Y S, ZHANG Z H. Degradation Prediction Model for Proton Exchange Membrane Fuel Cells . Based on Long Short-Term Memory Neural Network and Savitzky-Golay Filter［J］. International Journal of Hydrogen Energy, 2021, 46(29): 15928-15937.
	MA M, GUO Q, YAN C Q. ECT Image Reconstruction Algorithm Based on Generalized Regularization［J］. Journal of System Simulation, 2017, 29(8): 1851-1857+1872.
［3］	ZHANG M, XU Y, SOLEIMANI M. Quantitative Reconstruction of the Exterior Boundary Shape of Metallic Inclusions Using Electrical Capacitance Tomography［J］. IEEE Sensors Journal, 2017, 17(24): 8263-8270.
	MA M, ZHANG C X, JI J J, et al. An improved conjugate gradient algorithm for image reconstruction algorithm ［J］. Acta Metrologica Sinica, 2013, 34(1): 27-30.
［11］	张立峰, 王会忍. 基于卷积神经网络及有限元仿真的电容层析成像图像重建［J］. 系统仿真学报, 2022, 34(4): 712-718.
	ZHANG L F, ZHANG M. An Optimized Algorithm for Image Reconstruction of Electrical Capacitance Tomography［J］. Acta Metrologica Sinica, 2021, 42(9): 1155-1159.
	LI F, TAN C, DONG F. Fully Connected Deep Network Algorithm for Electrical Tomography［J］. Journal of Engineering Thermophysics, 2019, 40(7): 1526-1531.
［16］	马敏, 郭琪, 闫超奇. 基于广义正则化的ECT图像重建算法［J］. 系统仿真学报, 2017, 29(8): 1851-1857+1872.