Correct temporal averaging in gamma-ray tomography

The dynamic bias error is a well-known effect in transmission radiometry. It appears when scanned processes offering a high dense variability such as phase distribution in turbulent multi-phase flows. If phases vary strongly during the data acquisition, the projection data is inherent time-averaged. Because of the non-linear relation between attenuation and measured stochastic intensity, the calculation of the classic time-averaged attenuation from the time-averaged projection data by the attenuation law produces a non-negligible phase fraction deviation. In general, this leads to an underestimation of the real attenuation which equals an overestimation of the gas phase in tomography images of two-phase flows for instance.
There are several approaches for the correction of this so called dynamic bias error. Recently, a method for correct averaging in transmission radiometry was developed. The method does not take any a priori knowledge about the flow into account but considers the Poisson distributed emission process of the radiation source. By deconvolving the Poisson distribution from the measured intensity distribution, the distribution of the attenuation is obtained. This demands the solution of an ill-conditioned equation system.
In this contribution the application of the correct averaging method (CAM) on time-averaged gamma-ray tomography is demonstrated using a mock-up of a centrifugal pump. A highly turbulent two-phase flow scenario is simulated based on both a virtual tomography data set as well as real measured data. By applying CAM, an elimination of the systematic dynamic bias error could be achieved even for very small numbers of gamma photons.