An autoregressive model (AR model) based on empirical mode decomposition (EMD) and independent component analysis (ICA) was applied to identify gas-liquid two-phase flow regime. The dynamic differential pressure signals coming from Venturi tube were first processed with normalization and EMD. The intrinsic mode functions (IMFs) with high frequency component were denoised by wavelet packet. Then the dimension of IMFs was reduced through ICA. The independent components obtained from ICA were selected to establish the AR model. With model analysis

the coefficients and the variances of residual errors were defined as the eigenvector

and templates of different flow regimes were established. The flow regime was identified by calculating the synthetic Mahalanobis distance of eigenvectors between template and pressure fluctuation signal. The experimental results of gas-liquid two-phase flow in horizontal pipes with 40 mm inner diameter manifest that this method can identify bubble flow

slug flow and plug flow with an accuracy of 94.3%. This method can be realized easily for identification of flow regime in gas-liquid two-phase flow with less influence of environment.