Strain field imaging by applying anisotropic electrical impedance tomography on conductive surface coating

Measurement of mechanical strain on the surface of an object is important in areas such as structural health monitoring and tactile sensing applications. In this paper, the measurement of strain fields on surfaces using electrical impedance tomography (EIT) -based surface sensor, or sensing skin, is considered. Because mechanical strain generally leads to anisotropic changes in the electrical conductivity of the material, the particular focus is on anisotropic EIT imaging of the surface sensor materials. The anisotropic EIT reconstruction problem is written in the frameworks of Bayesian inference and non-linear difference (NLD) imaging, and the approach is validated with a numerical simulation study and experimentally. The simulation part of the study demonstrates the feasibility of the proposed approach for imaging anisotropic conductivity changes. Based on the simulation, in an ideal setup with low noise level, it is possible to detect features in the different components of an anisotropic conductivity change caused by mechanical strain. In the experimental part of the study, it is shown that the main features of a mechanical strain field can also be detected using EIT with real data. The experimental studies are conducted using a painted, elastic and conductive surface coating that is deformed by stretching and, for a reference, targeted with localized pressure using weights. In the former experiment, the anisotropic EIT reconstructions are qualitatively compared with strain field estimates obtained by digital image correlation (DIC) analysis applied to photographs of the surface. Despite some apparent uncertainties associated with the measurement setup, the results demonstrate that anisotropic EIT -based surface sensors can provide valuable information on mechanical strain fields.