油水混合物模态辨识与分类方法研究

Method of Identification and Classification of Oil-Water Mixtures

为提高原油脱水过程中宽量程含水率测量的精度,提出油水混合物多模态的含水率计算方法.通过分析油水混合物的不同状态,建立不同状态油水混合物的介电常数、电导率与原油含水率之间的关系,并基于核方法的自组织神经网络实现油水混合物的模式分类.实验结果表明,测量介电常数和电导率可以识别油水混合物的状态,及时修正含水测量仪的设置参数,提高宽量程原油含水率在线测量的精确度.

In order to improve the accuracy of measurement of wide range water content in the process of crude oil dehydration. Method of a computation based on the electrical measurement of multiple modes is proposed. Through analysis of different models of oil water mixture, relationship between the pattern and dielectric constant as well as conductivity is established. The multiple modes of oil-water mixture are classified based on self-organizing neural network based on kernel method. The experimental results showed that the different modes of oil-water mixture can be identified by measuring the permittivity and conductivity. Therefore, the setting parameters in the water content analyzer will be revised in time, and the on-line measurement accuracy of the water content can be effectively improved.