Open AccessFinite element mesh optimisation for improvement of the sensitivity matrix in electrical resistance tomography
Author(s) -
Xiao Liqing,
Xue Qian,
Wang Huaxiang
Publication year - 2015
Publication title -
iet science, measurement and technology
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.418
H-Index - 49
eISSN - 1751-8830
pISSN - 1751-8822
DOI - 10.1049/iet-smt.2014.0319
Subject(s) - polygon mesh , sensitivity (control systems) , finite element method , matrix (chemical analysis) , mesh networking , mesh generation , algorithm , topology (electrical circuits) , mathematical optimization , computer science , iterative reconstruction , condition number , tomography , mathematics , electronic engineering , materials science , artificial intelligence , engineering , structural engineering , eigenvalues and eigenvectors , physics , optics , telecommunications , computer graphics (images) , combinatorics , quantum mechanics , composite material , wireless
In electrical resistance tomography (ERT), finite element (FE) meshes of different topologies lead to different sensitivity matrices, which have great influence on the imaging quality of the ERT system. To improve the ill‐posedness of the traditional sensitivity matrix and thus to improve the image quality, the reciprocal of the sensitivity matrix condition number is designed as the fitness function, based on which the modified genetic algorithm is utilised to optimise the topology of the FE mesh offline, and the optimised FE mesh is used to generate the sensitivity matrix, which is thereafter applied to image reconstruction using the modified Newton–Raphson algorithm. The feasibility of the proposed method is demonstrated in both simulation and prototype experiments. Comparisons among the mesh the authors optimised, the traditional mesh and meshes modified with other methods (all the meshes have the same number of nodes and elements) show that the proposed method has obviously reduced the condition number of the sensitivity matrix, and thus enhanced the imaging quality.