A Prediction Method of Five-Axis Machine Tool Energy Consumption with GBRT Algorithm

As the main carrier of the manufacturing industry, energy consumption of machine tools has been studied by more and more scholars. In this paper, a new method to predict energy consumption of five-axis machine center is proposed. Firstly, the energy consumption model of each component is established under the unload condition. Then the model of milling energy is established based on the gradient boosting regression tree (GBRT) algorithm, and the importance of each processing parameter on energy consumption is analyzed. Finally, a milling experiment is used to verify the accuracy of the model.