Abstract
With the increase of spindle speed, heat generation becomes the crucial problem of high-speed motorized spindle. In order to obtain the actual thermal behavior of a motorized spindle, a digital twin system for thermal characteristics is developed in this paper. The mechanism of digital twin for thermal characteristics is to simulate the thermal behavior of a machine tool through mapping and correcting the thermal boundary conditions using the data acquisition system and correction models. The proposed digital twin system includes three modules which are the digital twin software, the data acquisition system, and the physical model with embedding sensors. The digital twin software is developed based on the Qt with the C + + programming language and the secondary development of ANSYS. Correction models for thermal boundaries are proposed to correct the heat generation and thermal contact resistance using the temperatures measured by the data acquisition system at thermal key points. To verify the prediction accuracy of the digital twin system, an experiment is carried out on a motorized spindle. The experimental results show that the prediction accuracy of the digital twin system is greater than 95%. It is of great significance to improve the accuracy of thermal characteristics simulation and thermal optimization.
Highlights
Thermal behavior prediction is significant in thermal optimization of Computer Numerical Control (CNC) machine tools
The experimental results show that the prediction accuracy of the digital twin system is greater than 95%
The results show that the prediction accuracy of the proposed digital twin system for thermal behavior is greater than 95%, it is of great significance to improve the accuracy of thermal analysis and thermal optimization of CNC machine tools
Summary
Thermal behavior prediction is significant in thermal optimization of Computer Numerical Control (CNC) machine tools. The motorized spindle is the core and a main heat source of CNC machine tools. The main factors that affect the accurate prediction of the temperature field and thermal deformation of the spindle come from two aspects, heat generation and thermal contact resistance, both of which are not constant during the working process of the spindle. Owing to the heat generation goes with it as spindle works which cause the thermal deformation, the thermal stress between the contact surfaces of the spindle's components is engendered, and the Thermal Contact Resistance (TCR) and the heat generated by internal heat sources change with the change of contact pressure. In order to improve the prediction accuracy of thermal behavior, digital twin for thermal characteristics becomes the best choice that is helpful in simulating the temperature field distribution of spindle unit
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