Digital twin driven thermal error control of linear axis for face gear grinding machine tool
The face gear transmission system offers advantages such as high interchangeability, strong load capacity, and effective power distribution, making it suitable for defense applications. The machining accuracy of the face gear grinding machine tool is significantly affected by the geometric and thermal errors, leading to a reduced geometric precision of the machined face gear. The real-time performance and robustness of the geometric and thermal error compensation system are the key to realize the thermal error control. So far, the real-time performance of compensation system is weak, and the robustness is poor. To address the above challenges, the effect of the temperature changes on positioning accuracy is studied. Then the thermal error prediction model is established based on the error mechanism for the linear axis of face gear grinding machine tool. Finally, the digital twin-driven thermal error control system is developed. The thermal error model is embedded into the digital twin-driven geometric and thermal error control system to realize the thermal error compensation of linear axis for face gear grinding machine tool. With the implementation of the digital twin-driven thermal error control system, the left tooth surface error decreased from 21.8 μm to 5.9 μm, and the right tooth surface error decreased from 22.9 μm to 5.7 μm, confirming the effectiveness of the proposed method.
Authors
- Chi Ma (ORCID: https://orcid.org/0000-0002-4168-036X)
- Jialan Liu (ORCID: https://orcid.org/0000-0002-0425-728X)
- Giovanni Totis (ORCID: https://orcid.org/0000-0002-2474-7489)
- Mingming Li (ORCID: https://orcid.org/0000-0001-8887-9299)
Institutions
- University of Udine (IT)
- Chongqing University (CN)
- Chang'an University (CN)
- Shenzhen Academy of Aerospace Technology (CN)
Publication Details
- Journal
- Procedia CIRP
- Published
- 2025-01-01
- DOI
- https://doi.org/10.1016/j.procir.2025.02.075
- Citations
- 1
- Primary Topic
- Iterative Learning Control Systems
- Type
- article
- Field-Weighted Citation Impact
- 1.21