Flow Pattern Identification of Fluctuating Vibration Gas-liquid Two-phase Flow based on ICEEMDAN and SVM
In order to solve the problem that the differential pressure signals of gas-liquid two-phase flow under fluctuating vibration conditions were too complicated and difficult to identify,a flow pattern identi-fication method based on the improved complete ensemble empirical mode decomposition with adaptive noise(ICEEMDAN)and support vector machine(SVM)was proposed.The ICEEMDAN was used to decompose the pressure difference signal after wavelet denoising.The Spearman correlation coefficient was calculated by the obtained each intrinsic mode functions(IMF)and the original signal.The IMF compo-nent with large correlation coefficient was selected for Hilbert transformation.The instantaneous amplitude of each transformed IMF component was calculated by energy entropy,singular spectrum entropy and power spectrum entropy,and then the feature vector was formed and brought into the support vector machine for flow pattern identification.The results show that this method can effectively identify bubble flow,slug flow,churn flow and annular flow in the state of fluctuating vibration,and the accuracy of identification can reach 95％.
NETL
NSTL
万方数据
