Modified Sparse Quasi - Newton Algorithm for Electrical Capacitance Tomography System

Authors

Chen Yu, College of Information and Computer Engineering of Northeast Forestry University, Harbin 150040, China;
Zongji Xia, College of Information and Computer Engineering of Northeast Forestry University, Harbin 150040, China;
Yujia Zhou, College of Information and Computer Engineering of Northeast Forestry University, Harbin 150040, China;

Abstract

Abstract: To solve the 'soft-field' nature and the ill-posed problem in electrical capacitance tomography technology, a modified sparse quasi - newton algorithm for electrical capacitance tomography is presented. The mathematical model of modified sparse quasi - newton is derived. The final iteration formula of modified sparse quasi - newton used to adjust the inverse problem solving of the capacitance tomography image reconstruction is given. An iterative formula for ECT inverse problem solving is used for digital simulation experiment. The simulation experiment results are compared with the results of LBP, Landweber, CG, SD, and so on. The results of the analysis show that both precision and speed of the algorithm are very good.

Recommended Citation

Yu, Chen; Xia, Zongji; and Zhou, Yujia (2019) "Modified Sparse Quasi - Newton Algorithm for Electrical Capacitance Tomography System," Journal of System Simulation: Vol. 31: Iss. 5, Article 1.
DOI: 10.16182/j.issn1004731x.joss.17-0287
Available at: https://dc-china-simulation.researchcommons.org/journal/vol31/iss5/1

First Page

819

Revised Date

2017-09-11

DOI Link

https://doi.org/10.16182/j.issn1004731x.joss.17-0287

Last Page

827

CLC

TN911.73

Recommended Citation

Chen Yu, Xia Zongji, Zhou Yujia. Modified Sparse Quasi - Newton Algorithm for Electrical Capacitance Tomography System[J]. Journal of System Simulation, 2019, 31(5): 819-827.

DOI

10.16182/j.issn1004731x.joss.17-0287