本文利用差压波动信号对水平管气液两相流流型辨识问题进行了研究。
Flow regime identification in horizontal gas- liquid two- phase flow using differential pressure signal is investigated in this paper.
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。
This dissertation focuses on the application of data fusion in two-phase flow regime identification.
试验结果表明所提出方法有效地抑制了高斯有色噪声对信号的影响，取得了良好的流型辨识效果。
The experimental results show the proposed method can suppress Gaussian noises of signal and is effective for flow pattern identification.
对于层状流、核心流、环状流、均相流等流型，流型辨识的准确率高于95%，辨识一个流型所用的时间小于0.3秒。
The accuracy of flow pattern identification of stratified flow, annular flow, core flow and homogeneous flow is more than 95% and the speed of flow pattern identification is less than 0.3s.
研究结果表明，该方法辨识精度高、辨识速度快，是两相流流型在线辨识的一种有效手段。
Research results show that the new method has good identification precision, fast identification speed, it is an effective tool for two-phase flow pattern on-line identification.
研究结果表明，该方法辨识精度高、辨识速度快，是两相流流型在线辨识的一种有效手段。
Research results show that the new method has good identification precision, fast identification speed, it is an effective tool for two-phase flow pattern on-line identification.
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