A method of flow regime identification based on empirical mode decomposition was proposed.
提出了一种基于经验模式分解的气液两相流流型识别方法。
This dissertation focuses on the application of data fusion in two-phase flow regime identification.
将数据融合技术应用于流型辨识研究，对其中的层次、结构等问题进行了深入的探讨。
However this method easily makes a confusion in flow regime identification owing to the influence of gas speed.
由于这一技术受到气泡流速的影响，容易造成流型识别的混淆。
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