Background: The flow patterns of two phase flow will directly influence the heat transfer and mass transfer of the flow.Purpose: By wavelet analysis of the pressure drop experimental data

the wavelet coefficients of different frequency can be obtained.Methods: Get the wavelet energy and then train them in the model of BP neural network to distinguish the flow patterns.Introduced the implant gray neural networks model and use it for the two phase flow for the first time.At the same time

set up the method of training the pressure data and wavelet energy data in the support vector machine.Results: Through treatment of the gray layer

the result of the neural network is more accuracy.It can obviously reduce the effect of data marginalization.The accuracy of the pressure drop Lib-SVM method is 95.2%.Conclusions: The results show that these three methods can make a distinction among the different flow patterns and the Lib-SVM method gets the best result

then the gray neural networks

and at last the BP neural networks.