Deformation prediction model for milling residual stresses in complex thin-walled parts with variable curvature
Complex thin-walled parts with variable curvature are crucial in aerospace, yet their manufacturing-induced residual stresses often lead to deformation, posing challenges in surface residual stress measurement and deformation prediction due to the complex geometric coordinate system. This study develops a model for predicting the distribution of subsurface residual stresses and the resulting deformation. By integrating the segmented polynomial fitting and random forest regression methods, a subsurface residual stress distribution prediction model is established and verified through experiments on machining and stress detection of such parts. Additionally, a special fixture for stress detection is designed. Based on ABAQUS software, a deformation simulation model considering residual stress is developed. Through continuous two-month monitoring of parts with different processing parameters, it is found that the simulation results align with the experimental trend, with an error range of 6.7 %–12.4 %. Eventually, a deformation prediction model based on process parameters is constructed, which can effectively predict the deformation of these parts and provides a theoretical foundation for deformation control.
Authors
- Fupin Hu (ORCID: https://orcid.org/0000-0002-4493-0619)
- Zhijian Lin
- Chao Luo
- Chongjun Wu (ORCID: https://orcid.org/0000-0001-7529-2747)
- Xiaohui Jiang
- Ermakov Boris Sergeevich
Institutions
- University of Shanghai for Science and Technology (CN)
- Donghua University (CN)
- Peter the Great St. Petersburg Polytechnic University (RU)
- Genertec Shenyang Machine Tool Co., Ltd. (China) (CN)
Publication Details
- Journal
- Journal of Manufacturing Processes
- Published
- 2025-02-18
- DOI
- https://doi.org/10.1016/j.jmapro.2025.02.032
- Citations
- 13
- Primary Topic
- Advanced machining processes and optimization
- Type
- article
- Field-Weighted Citation Impact
- 9.27
Funders
- National Natural Science Foundation of China
- Science and Technology Commission of Shanghai Municipality