Dynamic Tomography Techniques for Industrial Process Applications

Eric F. Oliveira1*, Silvio B. Melo2, Carlos C. Dantas2, Karlos A.N. Guedes2 and Emerson A.O. Lima3

1Instituto Federal de Alagoas- AL101, Maragogi-AL, Brazil.

2Universidade Federal de Pernambuco –A. Prof. Luis Freire, S/N – CDU, Recife-Pernambuco, Brazil.

3Universidade de Pernambuco (Poli)-R. Benfica, 455 - Madalena, Recife - PE, Brazil.

*efofisica@gmail.com

ABSTRACT

The state of the art methods applied to industrial processes is currently based on the principles of classical tomographic reconstructions developed for tomographic patterns of static distributions, or is limited to cases of low variability of the density distribution function of the tomographed object. One of the objectives of the present work is to discuss the difficulties that arise from implementing reconstruction algorithms in dynamic tomography that were originally developed for static distributions. Another objective is to propose solutions that aim at reducing a temporal type of information loss caused by employing regular acquisition systems to dynamic processes. With respect to dynamic image reconstruction it was conducted a comparison between the static reconstruction methods: MART (Multiplicative Algebraic Reconstruction Technique) and FBP (Filtered Back Projection), when used for dynamic scenarios. This comparison was based on a MCNPx (Monte Carlo N-Particle eXtended) simulation as well as an analytical setup of an aluminium cylinder that moves along the section of a riser during the process of acquisition, and also based on cross section images from CFD (Computer Fluid Dynamics) techniques. As for the adaptation of current tomographic acquisition systems for dynamic processes, this work established a sequence of tomographic views in a just-in- time fashion for visualization purposes, using false colours. Finally, a motion correction technique used in the medical field was proposed for industrial applications manipulating the weight matrix in the algebraic method.

Keywords Industrial Dynamic Tomography, Flow Dynamics,Dynamic Process Simulation, Dynamic Tomographic Reconstruction, Temporal Regularization