首页|基于幅度和相位融合的微波两相流测量系统设计

基于幅度和相位融合的微波两相流测量系统设计

扫码查看
针对油井开采过程中需要对各相含量进行精确预测以调整开采策略的实际问题,设计了 一种基于微波法的油水两相流检测系统.该系统利用微波在不同介质中透射能力的差异,构建了 一套包含微波信号源、功率放大器、功率分配器、检波器和STM32F103ZET6核心板的硬件电路系统,通过编写AD采集和串口通信的软件代码,来接收检波器端幅度和相位数据.在数据处理方面,分别对幅度数据、相位数据和幅度-相位融合数据采用BP神经网络的方法预测含水率.实验表明:在使用融合数据时,预测准确度可以提高至96.33%,取得了较理想的效果.
Design of Microwave Two-phase Flow Measurement System Based on Amplitude and Phase Fusion
To address the practical problem of accurately predicting the phase content in oil well production for optimizing ex-traction strategies,a microwave-based oil-water two-phase flow detection system was designed.This system utilized on the differences in microwave transmission capabilities across different media and built a hardware circuit system including a microwave signal source,power amplifier,power distributor,detector,and STM32F103ZET6 microcontroller.By writing AD acquisition and serial communication software codes,amplitude and phase data from the detector end were received.For data processing,BP neural net-work method was employed to predict water cut based on amplitude data,phase data,and amplitude-phase fusion data separately.Experimental results show that when using fused data,the prediction accuracy can be improved to over 96.33%,achieving an ide-al effect.

amplitude and phase fusionmicrowave methodtwo-phase flowwater contentBP neural networkAD collection

李利品、代雷、黄燕群、卢宇、颜曌恩

展开 >

西安石油大学,陕西省油气井测控技术重点实验室

西安现代控制技术研究所

幅度和相位融合 微波法 两相流 含水率 BP神经网络 AD采集

国家自然科学基金国家自然科学基金陕西省自然科学基金西安石油大学研究生创新与实践能力培养计划资助2023年陕西省学位与研究生教育研究项目

41874158519742502023-JC-YB-343YCS23214243SXGERC2023086

2024

仪表技术与传感器
沈阳仪表科学研究院

仪表技术与传感器

CSTPCD北大核心
影响因子:0.585
ISSN:1002-1841
年,卷(期):2024.(5)