| Abstract: | Horizontal oil-water two-phase flow widely exists in petroleum and chemical engineering industry, where the oil and water are usually transported together. As one of most importance process parameters to describe the two-phase flow, the flow pattern can reflect the flow characteristics of inner flow structure and phase distribution. The identification of flow pattern will contribute to develop more accurate measurement model for flow rate or phase fraction and ensure the safety and efficiency of operation in industry. A dual-modality sensor combining with continuous wave ultrasonic Doppler sensor (CWUD) and auxiliary conductance sensor, was proposed to identify flow patterns in horizontal oil-water two-phase flow. In particular, the oil-water flow characteristic was analyzed from Doppler spectrum based on the CWUD sensor. Besides, the dimensionless voltage parameter based on conductance sensor was applied to provide the information of continuous phase in the fluid. Several statistical features were directly extracted without any complicated processing algorithm from Doppler and conductance signals. The extracted features are put into a multi-classification Support Vector Machine (SVM) model to classify five oil-water flow patterns. The results show that the overall identification accuraccy of 94.74% is satisfactory for horizontal oil-water two-phase flow. It also demonstrates that the noninvasive ultrasonic Doppler technique not only can be used for flow velocity measurement but also for flow pattern identification. |
