A rapid modelling method for machine tool power consumption using transfer learning

Abstract Accurate power consumption models are the basis for improving energy efficiency of machine tools. The acquisition of energy consumption characteristics of different machine tools requires a large number of calibration experiments, which leads to low modelling efficiency. This paper proposes a rapid modelling method using transfer-learning to obtain the power consumption model of the target machine tool. After obtaining the power consumption model of the source machine tool through detailed experiments, this method only needs a few experiments to obtain the power consumption model of the target machine tool, which greatly improves the modelling efficiency, and the method is experimentally verified on different machine tools.