The Velocity Measurement of Two-phase Flow Based on Particle Swarm Optimization Algorithm and Nonlinear Blind Source Separation

吴新杰; 崔春阳; 胡晟; 李志宏; 吴成东

doi:10.1016/S1004-9541(12)60397-8

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The Velocity Measurement of Two-phase Flow Based on Particle Swarm Optimization Algorithm and Nonlinear Blind Source Separation

SELECTED PAPERS FROM THE 6TH WORLD CONGRESS ON INDUSTRIAL PROCESS TOMOGRAPHY (WCIPT6) | Updated：2026-01-06

- The Velocity Measurement of Two-phase Flow Based on Particle Swarm Optimization Algorithm and Nonlinear Blind Source Separation
- Chinese Journal of Chemical Engineering Vol. 20, Issue 2, Pages: 346-351(2012)
- Affiliations：
  
  1. College of Physics, Liaoning University,Shenyang,China,110036
  2. Key Laboratory of Condition Monitoring and Control for Power Plant Equipment, Ministry of Education, North China Electric Power University,Beijing,China,102206
  3. School of Information Science and Engineering, Northeastern University,Shenyang,China,110006
- Author bio：
- Funds：
- DOI：10.1016/S1004-9541(12)60397-8
  CLC：
- Published：2012
- Accepted：
Scan QR Code
WU Xinjie, CUI Chunyang, HU Sheng, LI Zhihong, WU Chengdong. The Velocity Measurement of Two-phase Flow Based on Particle Swarm Optimization Algorithm and Nonlinear Blind Source Separation[J]. , 2012, 20(2): 346-351.
DOI：

WU Xinjie, CUI Chunyang, HU Sheng, LI Zhihong, WU Chengdong. The Velocity Measurement of Two-phase Flow Based on Particle Swarm Optimization Algorithm and Nonlinear Blind Source Separation[J]. , 2012, 20(2): 346-351. DOI： 10.1016/S1004-9541(12)60397-8.

摘要

Abstract

In order to overcome the disturbance of noise

this paper presented a method to measure two-phase flow velocity using particle swarm optimization algorithm

nonlinear blind source separation and cross correlation method.Because of the nonlinear relationship between the output signals of capacitance sensors and fluid in pipeline

nonlinear blind source separation is applied.In nonlinear blind source separation

the odd polynomials of higher order are used to fit the nonlinear transformation function

and the mutual information of separation signals is used as the evaluation function.Then the parameters of polynomial and linear separation matrix can be estimated by mutual information of separation signals and particle swarm optimization algorithm

thus the source signals can be separated from the mixed signals.The two-phase flow signals with noise which are obtained from upstream and downstream sensors are respectively processed by nonlinear blind source separation method so that the noise can be effectively removed.Therefore

based on these noise-suppressed signals

the distinct curves of cross correlation function and the transit times are obtained

and then the velocities of two-phase flow can be accurately calculated.Finally

the simulation experimental results are given.The results have proved that this method can meet the measurement requirements of two-phase flow velocity.

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