Reconstruction of Electrical Tomography Images based on Parameter Estimation Method in Inverse Heat Transfer

Tomography is a non-invasive method that is used to visualize internal structure of an object. Electrical tomography is a method that recognizes the geometry of an object by applying voltage or current and using an image reconstruction algorithm. In spite of some advantages such as simplicity and low cost, reconstructed images by this method have low resolution and low quality. In addition to the system hardware, the reconstruction algorithms also reduces the quality of images. In this research, Levenberg – Marquardt Algorithm which is used to solve inverse heat transfer problems, is employed for image reconstruction in electrical tomography. In this technique, image reconstruction is perfomed by changing the thermal conductivity of material. Three different test cases are selected to investigate the capability of proposed algorithm in estimation of the unknown geometry and the results show that the Levenberg – Marquardt algorithm has ability to estimate unknown shapes. Sensitivity analysis is also performed in order to examine the effect of noise in detection of the unknown geometry. The results showe that with increasing the noise, the error created in the estimation of shape increases, but the estimated shape has good agreement with original geometry. Also, results of choosing different combinations of active sensors for applying thermal flux show that in addition to effectiveness of active sensors in increasing the accuracy of shape estimation, the unknown geometry can be estimated with two measurements.