Planar array magnetic induction tomography further improvement

摘要: Purpose Magnetic induction tomography (MIT) is a tomographic imaging technique with wide range of potential industrial applications. Planar array MIT convenient setup but unable to access freely from the entire periphery as it only collects measurements one surface, so remains challenging given limited data. This study aims assess use sparse regularization methods for accurate position and depth detection in planar MIT. Design/methodology/approach The most difficult challenges are solve inverse forward problems. The inversion severely ill-posed due Thus, this paper posed total variation (TV) problem solved efficiently Split Bregman formulation overcome difficulty. Both isotropic anisotropic TV formulations compared Tikhonov experimental data. Findings The results show that method failed or underestimated object depth. led recovery position. Originality/value There numerous applications where materials under testing restrict. Sparse promising approach improving