Improving the performance of gamma radiation based two phase flow meters using optimal time characteristics of the detector output signal extraction

Improving the performance of gamma radiation based two phase flow meters using optimal time characteristics of the detector output signal extraction

Blog Article

Measuring volume fractions and identifying the flow regime are important challenges in the oil industry.In the present study, three different flow regimes were simulated by MCNPX code.A 137Cs source and two NaI detectors have been used in order to count the transmitted photons.

The counted data had high-frequency noises.In order to tackle this problem, a Savitzky-Golay filter was COQ10 300MG applied.Therefore, four features in the time domain including STD, Skewness, Kurtosis, and Maximum Value were extracted.

It was found that the extracted features are not capable of separating the flow regimes completely, without overlap.Accordingly, three different features from registered data of both detectors were extracted.After investigating all the possible statues, two ANNs were implemented to identify the flow regimes and predict the void fraction, respectively.

By applying this method, all Outdoor Chat Set the three flow regimes were correctly distinguished and void fraction was predicted with root mean square error (RMSE) of less than 0.59.