For the conductance fluctuating signals measured from oil/water two-phase upward flow in a vertical pipe

11 feature selections reflecting flow characteristics of oil/water two phase flow were extracted.The feature selections in frequency domain were derived by using the linear prediction method of speech signal processing and the feature selections in time domain were derived by the time series statistical analysis.All extracted features were taken as the input of artificial neural network

at the total flow rate ranging from 10 m38226;d-1 to 60 m38226;d-1 and water cut from 51％ to 91%

the prediction model of artificial neural network based on the Levenbery-Marquardt algorithm was used and good water cut prediction results of oil/water two-phase flow were obtained.This study provided a new way to measure the phase volume fraction of two phase flow by soft sensor.