Toward a Volume Tomography Multimodal System Based on ECT Sensor
Q. Marashdeh, W. Warsito, and L. S. Fan
Department of Chemical and Biomolecular Engineering, The Ohio State University, Columbus, OH 43210, USA
The use of electrical tomography systems for process measurement and control has attracted increased attention in recent years. Modalities in electrical tomography are defined based on the sensor type used for acquiring the interrogating signal. The most popular modalities in this regard are electrical capacitance tomography (ECT), and electrical impedance tomography (EIT). The ECT sensor has the advantage of its non-invasive nature when compared to the EIT sensor. However, the use of ECT sensor has been restricted to permittivity imaging due to the nature of different strategies followed for permittivity imaging and mainly based on current injection.
In this work, a new non-invasive sensing system capable of imaging permittivity as well as conductivity distributions based on the ECT sensor is introduced. A dual sensitivity matrix is generated for permittivity/conductivity reconstruction. The new system uses the neural network multi criterion objective functions reconstruction techniques for volume (3D) imaging. Reconstruction from synthetic data is provided in this presentation. The system is based on using time varying voltage signal as the interrogating signal.
Keywords ECVT, EIT, Volume tomography, Multimodal
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