Combination of X-ray tube and GMDH neural network as a nondestructive and potential technique for measuring characteristics of gas-oil–water three phase flows

In this investigation, a fan-beam photon attenuation based system, including one X-ray tube and two sodium iodide crystal detectors, combined with group method of data handling (GMDH) neural network is proposed to recognize type flow regime predict gas-oil–water volume fractions three phase flow. One GMDH was considered for recognizing patterns networks were implemented the fractions. The recorded energy spectra from detectors defined as inputs networks. pattern output obtained first other networks, respectively. Through application methodology, all recognized correctly except single case. fraction also predicted RMS error less than 3.1.