Paper
13 October 2008 Mass flow-rate measurement of oil-water two-phase flow based on differential pressure and adaptive wavelet network
Jun Han, Feng Dong, Wei Li, Yaoyuan Xu
Author Affiliations +
Abstract
Measurement of the oil-water flow is of great importance in the industrial process. In the paper, a soft-measurement method for oil-water mass flow-rate was brought forward, in which the V-cone differential pressure meter was used and the adaptive wavelet network was developed to achieve the soft-measurement of the mass flow-rate. The multi-input single output model of adaptive wavelet network was adopted to approximate the mass flow-rate of oil-water. The paper focused on the experimental measurement of the homogeneous model of oil-water two-phase flow in horizontal pipe. Experimental results showed that the soft-measurement method combined differential pressure with adaptive wavelet network could satisfy the demand of the mass flow-rate measurement and the measurement error of the mass flow-rate was relatively small. The measurement error of the total mass flow-rate was acceptable.
© (2008) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Jun Han, Feng Dong, Wei Li, and Yaoyuan Xu "Mass flow-rate measurement of oil-water two-phase flow based on differential pressure and adaptive wavelet network", Proc. SPIE 7128, Seventh International Symposium on Instrumentation and Control Technology: Measurement Theory and Systems and Aeronautical Equipment, 712817 (13 October 2008); https://doi.org/10.1117/12.806650
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Cited by 2 scholarly publications.
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KEYWORDS
Wavelets

Neurons

Data modeling

Neural networks

Control systems

Process control

Computing systems

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