An Image Reconstruction Algorithm for Electrical Capacitance Tomography Based on Robust Principle Component Analysis

Sensors

Jing Lei²  Shi Liu²  Xueyao Wang¹ 

[1] Institute of Engineering Thermophysics, Chinese Academy of Sciences, Beijing 100190, China; E-Mails:;Key Laboratory of Condition Monitoring and Control for Power Plant Equipment, Ministry of Education, North China Electric Power University, Beijing 102206, China; E-Mail:

关键词: electrical capacitance tomography;    capacitance sensor;    image reconstruction;    inverse problem;    robust principle component analysis;    forward-backward splitting technique;    alternating direction iteration optimization method;   

DOI  :  10.3390/s130202076

来源: mdpi

【 摘 要 】

Electrical capacitance tomography (ECT) attempts to reconstruct the permittivity distribution of the cross-section of measurement objects from the capacitance measurement data, in which reconstruction algorithms play a crucial role in real applications. Based on the robust principal component analysis (RPCA) method, a dynamic reconstruction model that utilizes the multiple measurement vectors is presented in this paper, in which the evolution process of a dynamic object is considered as a sequence of images with different temporal sparse deviations from a common background. An objective functional that simultaneously considers the temporal constraint and the spatial constraint is proposed, where the images are reconstructed by a batching pattern. An iteration scheme that integrates the advantages of the alternating direction iteration optimization (ADIO) method and the forward-backward splitting (FBS) technique is developed for solving the proposed objective functional. Numerical simulations are implemented to validate the feasibility of the proposed algorithm.

【 授权许可】

CC BY   
© 2013 by the authors; licensee MDPI, Basel, Switzerland.