Industrial gamma-ray tomographic scan method for large scale industrial plants

In this paper, a tomographic scan method with fixed installed detectors and a rotating gamma-ray source system is presented to diagnose industrial plants, which were impossible to examine by conventional tomographic systems. Monte Carlo simulations had been performed for two kinds of phantoms. Lab-scale experiments with the same condition as one of the phantoms, have been carried out. Algebraic and statistical reconstruction methods were applied for the reconstruction of simulation and experimental data. The reconstruction results from different algorithms were compared. Simulation results showed that reconstruction from the photopeak counting measurement gave better results than the gross counting measurement, although the photopeak counting measurement had large statistical errors. The statistical algorithm gives better results for tomographic scan methods than the algebraic method for the simulation data. Simulation and experimental data showed that this work demonstrates the feasibility of the fixed detection and rotating source system for scanning of industrial plants. Those results appear to be promising for industrial tomographic applications, especially for petrochemical industries.