Energy of Intrinsic Mode Function for Gas-Liquid Flow Pattern Identification
Energy of Intrinsic Mode Function for Gas-Liquid Flow Pattern Identification
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DOI：
10.2478/v10178-012-0067-y
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发表时间：
2012-12
影响因子：
1
通讯作者：
Zhi-qiang Sun;Hui Gong
中科院分区：
文献类型：
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作者：
Zhi-qiang Sun;Hui Gong
气液流广泛存在于各种工业过程中。正确识别气液流状态是多相流测量中最艰巨的挑战之一。在这里，我们提出了一种新的气液流动模式分类方法。在该方法中，基于本征模态函数的平均能量和气液混合物的体积空隙率构建流型图。使用经验模态分解技术从钝体上的压力脉动中提取本征模态函数。在环境温度和大气压下，以空气和水为工质，在气泡、塞子、段塞和环形流型中进行了实验。验证测试表明，所开发的流型图识别率超过90%。该方法适合实际应用中的气液流型识别。
Gas-liquid flows abound in a great variety of industrial processes. Correct recognition of the regimes of a gasliquid flow is one of the most formidable challenges in multiphase flow measurement. Here we put forward a novel approach to the classification of gas-liquid flow patterns. In this method a flow-pattern map is constructed based on the average energy of intrinsic mode function and the volumetric void fraction of gas-liquid mixture. The intrinsic mode function is extracted from the pressure fluctuation across a bluff body using the empirical mode decomposition technique. Experiments adopting air and water as the working fluids are conducted in the bubble, plug, slug, and annular flow patterns at ambient temperature and atmospheric pressure. Verification tests indicate that the identification rate of the flow-pattern map developed exceeds 90%. This approach is appropriate for the gas-liquid flow pattern identification in practical applications.