Establishment and Application of Drilling Temperature Prediction Model for Viscoelastic Materials
Viscoelastic materials have the properties of both elastic solid and viscous fluid.Traditional thermal analysis methods cannot accurately describe the simultaneous viscous and elastic deformation.The research of temperature field in material remov-al process is very rare according to the characteristics of the complex material.The machine learning algorithm is applied to the temperature prediction of the drilling of the drug string.Firstly,the nonlinear model is proved by linear regression fitting.Second-ly,the random forest and BP neural network algorithm were used for modeling.The random characteristics of the random forest model made it have a certain anti-noise ability,and the BP neural network model had the highest accuracy and the determina-tion coefficient reached 0.989.The prediction function of BP neural network model is used to prevent and control the processing process in advance,optimize the combination of processing parameters,and realize efficient and safe production.
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