Back to Search
Start Over
Multi-Objective Optimization Design of Dual-Spindle Component Based on Coupled Thermal–Mechanical–Vibration Collaborative Analysis.
- Source :
- Machines; Dec2024, Vol. 12 Issue 12, p885, 17p
- Publication Year :
- 2024
-
Abstract
- To comprehensively improve the thermal, static and dynamic characteristics and achieve lightweighting for CNC machine tools, this paper proposes a multi-objective joint optimization method based on coupled thermal–mechanical–vibration collaborative analysis. The dual-spindle component of a CNC machine tool is taken as the parameterized model. According to the theories of thermal characteristics, statics, and dynamics, the solution of thermal-mechanical coupling deformation and the solution of vibration characteristics under prestress are repeatedly conducted, that are working collaboratively with each process of parameters sensitivity computing, selection of design variables, central composite design, and multi-objective joint optimization. The response surfaces of the objective functions are established. The optimal parameter combination for improving CNC machine tool performance is effectively obtained. And the multiple objectives of improving the thermal, static and dynamic characteristics, as well as lightweighting, are achieved. The results show that the mass of the optimized component is reduced by 10.1%; the first-order natural frequency is increased by 3.9%; the coupling deformation of the end face of the left spindle seat is reduced by 5.3%; and the coupling deformation of the end face of the right left spindle seat is reduced by 9.0%, while the temperature of the component hardly increases. This indicates that this method can comprehensively improve the performance of CNC machine tool components and provide a reference for the multi-objective joint optimization design of CNC machine tools. [ABSTRACT FROM AUTHOR]
Details
- Language :
- English
- ISSN :
- 20751702
- Volume :
- 12
- Issue :
- 12
- Database :
- Complementary Index
- Journal :
- Machines
- Publication Type :
- Academic Journal
- Accession number :
- 181955216
- Full Text :
- https://doi.org/10.3390/machines12120885