中文摘要：

一个 slotted 孔在一个标准孔上有许多优势。为单相的流动测量，它的流量系数对在上游的速度分布图感觉迟钝。为二阶段流动大小，它的差压(DP ) 的各种各样的特征与气体和液体的集体流量稳定、密切相关。在信号特征和二阶段的流量之间的复杂关系通过背繁殖(BP ) 的使用被建立神经网络。实验与 50mm 在水平试管被执行内径，在 0.2m ( 3 )的范围与水流量操作了 .h (-1)到 4m ( 3 ) .h (在 100m ( 3 )的范围的-1),气体流速 .h (-1)到 1000m ( 3 ) .h (在 400kPa 和 850kPa 的-1),和压力分别地，在温度是环境温度的地方。这篇文章包括湿球气体流量计开发，试验性的矩阵，信号处理技术和完成的结果的原则。根据结果， slotted 孔结合一个训练神经网络，这被建议可以提供一个简单却有效的解决方案给湿球气体流量计开发。给词调音：湿球气体流量计；二阶段的流动；slotted 孔；神经网络；小浪分析；主要组分分析

英文摘要：

A slotted orifice has many superiorities over a standard orifice. For single-phase flow measurement, its flow coefficient is insensitive to the upstream velocity profile. For two phase flow measurement, various characteristics of its differential pressure （DP） are stable and closely correlated with the mass flow rate of gas and liquid. The complex relationships between the signal features and the two-phase flow rate are established through the use of a back propagation （BP） neural network. Experiments were carried out in the horizontal tubes with 50ram inner diameter, ooerated with water flow rate in the range of 0.2m^3·h^-1 to 4m3·h^-1, gas flow rate in the range of 100m^3·h^-1 to 1000m^3·h^-1, and pressure at 400kPa and 850kPa respectively, where the temperature is ambient temperature. This article includes the principle of wet gas meter development, the experimental matrix, the signal processing techniques and the achieved results. On the basis of the results it is suggested that the slotted orifice couple with a trained neural network may provide a simple but efficient solution to the wet gas meter development.