Data Mining Method Based on HHT and Application Research in Flow Regime Identification

Abstract

For identifying gas-liquid two-phase flow regime, a kind of data mining method based on Hilbert-Huang transform was put forward. At first, the dynamic differential pressure signal coming from Venturitube was handled by HHT, the instantaneous frequency, instantaneous swing and user-defined characteristic variable of different mode were calculated. The relation of characteristic variable and flow regime was obtained by visual analyzing instantaneous frequency and characteristic variable. Afterwards, according to the distribution of characteristic variable, fuzzy association rules of identifying flow regime was gained adopting data mining method, and the results of flow regime identification were acquire through fuzzy illation and calculation. The experimental results of gas-water two-phase flow in vertical pipes with 50mm and 40mm inner diameter show, this method could identify bubble flow, slug flow and churn flow effectively, and discriminating precision exceed 94%. The method's principle is easy, has few influence by experimental condition and good universality, and it could settle for practical flow regime identification