Phase discrimination in void fraction measurements via genetic algorithms
Phase discrimination in void fraction measurements via genetic algorithms
复制标题
通过遗传算法进行空隙率测量的相位辨别
DOI：
10.1063/1.1146130
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发表时间：
1995
期刊：
影响因子：
--
通讯作者：
A. Bombač
中科院分区：
文献类型：
--
作者：
I. Zun;B. Filipič;M. Perpar;A. Bombač
本文讨论了从传感器产生的时间依赖性原始信号重建流体动力学结构函数的困难。在存在两个流体相的情况下，传感器处的相界面的变形导致事件的发生与检测之间的滞后，并且由于若干原因，探针响应特性可能随时间改变。提出了一种基于人机交互和遗传优化的鉴相方法。为了区分相位，首先提出了两点阈值鉴别。此外，人机方法介绍，它可以模仿人类专家的原始信号的观察和他的直观的歧视过程。最后，遗传算法被用来搜索那些阈值设置，产生最接近那些由专家定义的解决方案。所提出的新方法能够适应特定的流动条件。
The paper deals with the difficulties of reconstructing a hydrodynamic structural function from a time‐dependent raw signal produced by a sensor. In the presence of two fluid phases, the deformation of a phase interface at a sensor leads to a lag between the occurrence and the detection of the event, and the probe response characteristics may be altered with time for several reasons. A new phase discrimination technique is presented based on man–machine interaction and utilizing genetic optimization. To discriminate the phases, two‐point threshold discrimination is proposed at first. In addition, a man–machine method is introduced which can mimic a human expert observation of a raw signal and his intuitive discrimination procedure. Finally, genetic algorithms are used to search for those threshold settings that produce solutions closest to those defined by an expert. The proposed new method is capable of adaptation to specific flow conditions.