Wax deposition rate model for crude oil pipeline based on neural network

In order to study the rule of wax deposition of Daqing oilfield crude oil in oil pipeline, an experimental unit is made by self. Based on experimental results, the relationship between the wax deposition rate and its influencing factors are established by using artificial neural network. The neural network is 4-7-1 BP structure, and the factors of influencing wax deposition rate include the shear stress, temperature gradient and molecular concentration gradient at pipeline wall, and dynamic viscosity of the crude oil. The predicted result shows that Prediction precision is high, error is less than 2%.