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Nondestructive Position Detection of a Metallic Target within Soil Substrate Using Electromagnetic Tomography

To determine the position of a metallic target in a cylindrical background made of soil, the electromagnetic tomography, as a nondestructive method, is employed. It is a difficult goal to produce precise electromagnetic tomography images using analytical methods. To cope with this issue, an artificial neural network is trained to mimic the electromagnetic tomography system. A hybrid optimization algorithm, which is a combination of intelligent global harmony search and Levenberg–Marquardt algorithms, is proposed to optimize the artificial neural network weights and biases. Simulation results show that the proposed method can estimate the position of target with an acceptable accurately.

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