基于压缩感知算法的平面电容成像图像重建

doi:10.3969/j.issn.1000-1158.2023.08.11

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Abstract Image reconstruction algorithm based on compressed sensing theory is proposed for planar electrical capacitance tomography (PECT). According to the relation between capacitance measurements of the planar array electrode and the distance between the electrode pairs,the number of independent measurements is cut down. Based on the ill conditioned characteristics of image reconstruction and the sparsity of dielectric constant of defect model,the gradient projection (GPSR-BB) algorithm based on compressive sensing theory is applied to PECT. The simulation and experiment of composite defect detection are carried out using GPSR-BB algorithm and compared with LBP algorithm,Tikhonov regularization algorithm and Landweber algorithm. Results show that the quality of reconstructed images is obviously improved.

Key words： metrology;planar electrical capacitance tomography;image reconstruction;compressed sensing multiphase flow distribution

Received: 16 March 2022 Published: 22 August 2023

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TB937

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	Articles by authors
	ZHANG Li-feng
	ZHANG Bo-xiong
	HUA Hui-chun

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ZHANG Li-feng,ZHANG Bo-xiong,HUA Hui-chun. Image Reconstruction of Planar Electrical Capacitance Tomography Based on Compressed Sensing Algorithm[J]. Acta Metrologica Sinica, 2023, 44(8): 1222-1228.

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http://jlxb.china-csm.org:81/Jwk_jlxb/EN/10.3969/j.issn.1000-1158.2023.08.11 OR http://jlxb.china-csm.org:81/Jwk_jlxb/EN/Y2023/V44/I8/1222

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