【作者】 石岗； 耿艳峰；

【Author】 SHI Gang GENG Yan-feng College of Information and Control Engineering,China University of Petroleum,Dongying 257061,China

【机构】 中国石油大学信息与控制工程学院；

【摘要】 为了精确测量凝析天然气的气液相流量,研究了将神经网络用于气液两相流流量测量的方法。以中国石油大学自动化系试制的流量检测仪表样机为硬件基础,分析了仪表的差压波动信号,并通过比较F比值确定了特征提取方法。根据多相流存在多种流型的特点,采用了首先识别流体流型再计算其流量的方法。研究表明:神经网络在凝析天然气流量测量中具有较大的应用潜力。但要获得较高的层量精度,还需要更为准确的信号特征提取方法以及更加合理的网络结构。更多还原

【Abstract】 Neural network are used for wet gas flow measurement with high precision.Differential pressure signals from the flowmeter proto- type developed by the Claim University of Petroleum are analyzed. Different techniques for feature extraction are studied and their F ratios compared. Considering the characteristic of wet gas that has different flow patterns,a process that identifies flow pattern first and then calcu- lates flow rate is adopted.The research shows that:neural network can be used in the wet gas flow measurement with satisfactory results.The gas phase error reached 10 %. Accurate ways for feature extraction and rational network structure both play an important role in the measure- ment.更多还原