Dual imaging modality of granular flow based on ECT sensors

In this study, a previously developed dual modality imaging system is applied to image the flow of granular matter with different electrical properties in cylindrical vessels. The imaging system is based on both capacitance and power measurements acquired by an electrical capacitance tomography (ECT) sensor located around the vessel. The measurement data are then used to reconstruct cross-sectional images of both permittivity and conductivity distributions. A neural network multi-criterion optimization reconstruction technique (NN-MOIRT) is used for the inverse (reconstruction) problem. The contribution of this technology to the field of granular matters is explored through review of research articles that can be a direct application of this development. We discuss the capabilities of this dual-modality acquisition system using synthetic data for granular matter with different electrical properties.