Multi-source data based refined transient modelling and analysis method for thermal performance of precision machine tool feed system
Variation in feed speed, acceleration, preload and other parameters significantly influence the inertia loss torque and friction torque within the feed system of machine tool. These alterations directly impact the heat generation power (HGP) of each component, which consequently determines the therm...
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| Main Authors: | , , , , , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Elsevier
2025-09-01
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| Series: | Case Studies in Thermal Engineering |
| Subjects: | |
| Online Access: | http://www.sciencedirect.com/science/article/pii/S2214157X25009554 |
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| Summary: | Variation in feed speed, acceleration, preload and other parameters significantly influence the inertia loss torque and friction torque within the feed system of machine tool. These alterations directly impact the heat generation power (HGP) of each component, which consequently determines the thermal boundary conditions and the temperature field of the feed system, ultimately affecting thermal error. Traditional heat generation model (THGM) calculates the HGP based on constant running parameters, neglecting the dynamic changes in inertia loss torque and friction torque during the feeding process. This study proposes a transient refined heat generation model (RHGM) based on multidimensional data fusion. RHGM incorporates real-time fluctuations in key parameters of the feed system, including inertial force, speed and preload. RHGM demonstrates that the motor input power is dynamically balanced with the HGP of the components and the inertial force power. Simulation and experimental results validate that RHGM yields significant improvements. Specifically, RHGM reduces temperature deviations by 9.6 %–21.2 % compared to THGM. Moreover, the thermal deformation deviation in RHGM is reduced by up to 58.6 % relative to THGM. RHGM can provide reference and guidance for subsequent research on thermal error compensation and control in machine tools. |
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| ISSN: | 2214-157X |