Charge distribution around a rising bubble in a two-dimensional fluidized bed by signal reconstruction

A signal reconstruction technique was developed recently to measure the electrostatic charge density distribution surrounding a bubble rising in a two-dimensional gas–solid fluidized bed using four induction probes flush with the outside wall of a two-dimensional fluidized bed and connected to charge amplifiers for recording induced charge signals as bubbles pass by the probes. The model was implemented in Visual FORTRAN using the LSGRR Subroutine to invert the matrix for the signal reconstruction. However, if the matrix was mathematically singular or ill-conditioned, a least-squares routine or the singular value decomposition routine provided had to be used to give approximate results. If the dimension of the matrix exceeds the permissible limit, or the number of pixels is much larger than the number of measurements, the matrix cannot be inverted using the LSGRR subroutine.This paper shows that an iterative linear back projection algorithm (LBP), often used in linear tomography, can be applied to improve the reconstruction resolution of the charge distribution around rising single bubbles in a gas–solid fluidized bed. The experimentally measured induced charges from four induction probes were then applied to reconstruct the real charge distribution around a single rising gas bubble injected in a two-dimensional column as it passed the probes. The results reconstructed using the LBP method are found to be smoother and more accurate than those obtained from the LSGRR subroutine.

Charge density distribution around a gas bubble in a fluidized bed of dielectric particles was reconstructed using the iteration linear back projection (LBP) algorithm based on induced charge signals from 4 dynamic probes. The probe size does not influence the reconstruction resolution greatly, with an optimal diameter ranging from 3-6 mm for the probe arrangement used in the current study.Figure optionsDownload as PowerPoint slide