Research on the digital twin for thermal characteristics of motorized spindle

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.

Digital Twin-Driven Thermal Error Prediction for CNC Machine Tool Spindle

“…Ma et al presented a self-learning-empowered thermal error prediction approach for machine tools based on DT [15]. Xiao et al developed a DT system to analyze the thermal characteristics of the MT spindle [16]. Liu et al designed an error prediction model for the MT spindle using DT [17].…”

Fast electrothermal coupling calculation method for supporting digital twin construction of electrical equipment

“…where n f is the number of boundary face of Ω i , x GP j is the centre (Gaussian point) of jth boundary face, whose area and outward unit normal are denoted as S j and ñj , respectively. From Equation (15), it is easy to prove that B Ω i is a constant matrix in Ω i , which means J and q are constant vectors in one SD according to Equation ( 14). This is an important concept.…”

“…In the novel algorithm, we first establish the SD and then calculate the B Ω i matrix for each SD according to Equation (15) and loop by the SD to calculate the stiffness matrix and load vector through Equations ( 18) and ( 23) without involving complex integral operations and parent element mapping.…”

“…Step 2: According to the number of CPU cores, SD is processed cyclically. Each core calculates and stores the B Ω i using Equation (15) and then calculates each SD stiffness and load vector according to Equations ( 18) and (23).…”

“…The second is to build a DT model through the multiphysics model and use fast numerical methods to update the internal state of DT [7,13,14]. The multi-physics calculation method employed in DT mostly adopts the conventional finite element method (CFEM) [13,15,16]. For a complex electrical equipment, a large number of grids are often required to ensure the accuracy of the calculation.…”