基于EEMD-Hilbert谱的气液两相流钝体绕流流型识别

为了有效识别气液两相流的流型,以水和空气为实验介质,以涡街流量计为元件诱发钝体绕流,通过管壁差压法获取气液两相流钝体绕流的尾迹波动信号,采用集总经验模态分解对信号进行分解,通过Hilbert变换得到Hilbert边际谱,利用最大互相关系数法对固有模态函数进行筛选,选取特征固有模态函数能量比分别与体积含气率、两相雷诺数构建流型图。结果表明,构建的两类新流型图对单相水、泡状流、塞状流、弹状流等典型流型的识别率分别可达91.67%和88.89%,能较好地满足工程实际应用的需求。

Flow regime identification of gas liquid two phase flow with flow around bluff body based on EEMD Hilbert spectrum

In order to identify the flow regime of gas liquid two phase flow effectively, air and water are taken as the experiment media and a vortex flowmeter is employed as component to induce the flow around bluff body. The duct wall differential pressure method is adopted to acquire the wake fluctuation signals of the flow around bluff body in the gas liquid two phase flow. The signals are decomposed with the ensemble empirical mode decomposition, and then the Hilbert marginal spectrum is obtained with Hilbert transform. The maximum cross correlation coefficient method is used to sift the characteristic intrinsic mode functions. The energy ratios of the characteristic intrinsic mode functions are selected, and used to construct the flow pattern maps together with the volumetric void fraction and the two phase Reynolds number respectively. The results show that the two newly constructed flow pattern maps can successfully identify the typical flow patterns such as single phase water, bubble flow, plug flow and slug flow with the recognition rate up to 91.67% and 88.89% respectively, which can meet the needs of most practical engineering applications nicely.