Fast artifact filtering algorithm for electrical resistivity tomography

Abstract Owing to the ill-conditioned nature of electrical resistivity tomography and the measurement error of the hardware equipment, the reconstructed resistivity distribution image often contains artifacts of varying degrees. Other soft-field imaging technologies, such as electrical impedance tomography and electrical capacitance tomography, also encounter artifacts. Artifacts interfere with the assessment of damaged areas. To eliminate the influence of artifacts on the reconstructed image, a novel artifact elimination algorithm called the fast artifact filtering (FAF) algorithm is proposed. Based on the calculation results of existing algorithms, such as the Newton’s one-step error reconstructor (NOSER) algorithm, the FAF algorithm can remove the damaged areas with low confidence from the potentially damaged areas and only retain the damaged areas with high confidence for final imaging. Several simulation models were used to test the effectiveness of the artifact elimination algorithm proposed in this study. The test results show that the number of artifacts in the final reconstructed image is significantly reduced after the NOSER algorithm is combined with the FAF algorithm. In addition, when the number of finite element model division elements was 4802, the refresh time of a single image increased by approximately 1 ms. A structural health monitoring test for hollow structure is provided. The results show that the FAF also performs well on the measured voltage data.