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In most publications eddy current testing (ECT) methods are said to be suitable for surface defects up to several millimeters. This paper aims to evaluate the detection capabilities of eddy current testing based on two examples of modern approach. One of them is a harmonic eddy current method with use of wavelet transformation and neural network. The second method is pulsed eddy current testing (PECT) with use of evaluation script based on cross-correlation of measured data with the set of known reference signals. Two samples with five artificial defects each were investigated from the near and far side. Geometric parameters of every defect were then estimated. Results show that both methods are limited by the skin effect. However, the PECT with use of cross-correlation exhibits detection capabilities of subsurface defects in significant depth. On the other hand, harmonic eddy current testing shows lower errors in dimensions estimation for set of surface defects.
We present TomoTable—a research prototype of a position sensing device hidden inside an ordinary table. While the Human-Computer Interaction (HCI) field has extensively explored possibilities for spatially-aware multi-device interactions, the sensing methods that would enable such systems are still complex and hard to deploy in the wild. TomoTable presents a possibility of easily deployable invisible positional sensing that uses electrical capacitance tomography (ECT). Electrodes are embedded inside the table structure and provide accurate imaging of what is placed on the table. The entire system is invisible to the user. Objects can be identified based on their electrical properties. Our work creates opportunities for in-the-wild studies using multi-device systems. In this paper, we share the technical concept of TomoTable, preliminary insights on its use and perspectives for future studies.
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