Construction and testing of an electrical impedance tomography system for the investigation of conductive elastomers
Supervisor: Dr.-Ing. Johannes Mersch
Co-Supervisor: Univ.-Prof. Dr. Marco Da Silva
Electrical impedance tomography (EIT) is a fast, cost-efficient and non-invasive method for measuring and reconstructing the conductivity distribution of materials. These properties make EIT a suitable method for investigating the conductivity behaviour of elastomers under strain. In addition to applications in materials science, EIT is also used in medical imaging, process tomography and geophysics.
In the first section, the theoretical principles of electrical impedance tomography were presented. In particular, the difference between direct and inverse problems is explained here. The mathematically unstable nature of the inverse problem is illustrated by simulations and reconstructions of simple conductivity distributions.
An automated measurement system was developed which accelerates the process from entering the measurement parameters to performing the measurement and reconstruction with the library EIDORS. For this purpose, an interface was programmed in MATLAB, which communicates with the measuring device (ScioSpec ISX-3) via the COM port.
In order to better evaluate the different injection patterns, regularisation parameters and prior functions, measurements were carried out on a phantom (water tank) with known inhomogeneities. The results showed that the choice of reconstruction parameters has a significant impact on the quality of the reconstructed images.
Measurements were then carried out on elastomers with a conductive filling under different strain conditions. By applying suitable reconstruction parameters and comparing them with simulated strain states, physically plausible conductivity distributions were obtained. This shows that EIT is a promising tool for analysing conductivity distributions in elastomers under mechanical strain.
Keywords: Electrical impedance tomography, EIT, conductive elastomers, EIDORS
October 16, 2024