This paper focuses on the application of a recently proposed non-iterative inversion method for three different imaging techniques for two phases materials. Specifically, two techniques concern the retrieval of the resistivity of a conductor (electrical resistance tomography and magnetic induction tomography) and one technique concerns the retrieval of the permittivity of a dielectric material ...

In this work we apply the simulated annealing (SA) and genetic algorithms (GA) inversion methods to the reconstruction of permittivity images from electrical capacitance tomography (ECT) measurements. The forward problem (i.e., to find the mutual capacitance data for a given permittivity distribution in the sensor) is calculated by using a finite-volume space discretization method in order to a...

Accurate multiphase flow measurement is vital in monitoring and optimizing various production processes. Deep learning has as of late arose a promising approach for assessing flowrate dependent on customary meters. In this paper, we propose multi-modal sensor Temporal Convolution Network (TCN) based method to predict the volumetric oil/gas two-phase flows. The flowrates liquid gas phase vary fr...

The tomographic imaging of process parameters for oil-gas-water three-phase flow can be obtained through different sensing modalities, such as electrical resistance tomography (ERT) and electrical capacitance tomography (ECT), both of which are sensitive to specific properties of the objects to be imaged. However, it is hard to discriminate oil, gas and water phases merely from reconstructed im...

The global custody transfer market for liquefied natural gas (LNG) has grown at a strong pace in the last decade and use of LNG as transport fuel considerable environmental benefits. quantity is traded on basis energy transferred, calculated from volume, density gross calorific value. High-speed, accurate measurement therefore significant commercial electrical capacitance tomography (ECT) devic...

Biomass provides 10% of the global energy supply and electricity generation from biomass and waste is expected to increase by a factor of 4 by 2030. Currently efficiency of biomass power generation is poor and IEA targets improvements from 18% to 25% by 2030 [1]. Such increases in efficiency will require significant new technology and accurate real-time measurement of the flow of these highly v...