Combing mobile electrical capacitance tomography with Fourier neural operator for 3D fluidized beds measurement

Abstract Despite the practical importance, 3D measurements of gas–solid distribution in fluidized beds calls for further breakthroughs. Here an approach combing a recently developed mobile electrical capacitance tomography (ECT) sensor with Fourier Neural Operator (FNO) is developed, in which the fluidized bed is divided into a series of cross‐sectional slices along axial direction. At any given instant, the gas–solid distribution in one slice is measured by mobile ECT and the others, meantime, are predicted by FNO pre‐trained using experimental data. We verified this approach via computational fluid dynamics (CFD) simulations and experimental measurement of static object (i.e., cone, cylinder, and sphere) in fluidized bed. Following we applied this approach to direct measure 3D gas–solid distribution in a bubbling fluidized bed, and found that satisfactory image correlation coefficients and solid concentration average absolute deviation could be obtained, which indicates the proposed approach is promising for 3D fluidized bed measurements.