ACTA AERONAUTICAET ASTRONAUTICA SINICA >
Residual stresses evolution mechanism of thin⁃walled component and deformation control method
Received date: 2023-07-25
Revised date: 2023-08-17
Accepted date: 2023-10-07
Online published: 2023-12-01
Supported by
National Natural Science Foundation of China(52205501);Key Laboratory of High Performance Manufacturing for Aero Engine (Northwestern Polytechnical University), Ministry of Industry and Information Technology(HPM-2021-04);The High-level Talent Program of Yangzhou University(137012319);Yangzhou-Yangzhou University Cooperative Innovation Technology Platform Support Project(YZ2020266)
Deformation is one of the most important challenges in the machining of the thin-walled component, especially for the complicated thin-walled component with difficult-to-machining material. The internal stress and machining induced residual stress are evolved during the machining process, causing the poor machining accuracy of the final component. To solve this problem, a deformation control method based on the evolution mechanism of residual stress is proposed. Firstly, the simplified model of the component is obtained through the slice method. The equilibrium equation for clamping point is established by analyzing the loads distribution. The geometric equilibrium equation is then obtained according to the deformation superposition principle and micro deformation theory. The distribution of loads at different instants of machining process is analyzed, and the evolution mechanism of the residual stresses and the equivalent loads is revealed. Secondly, a mathematical model is established to regulate the in-process deformation of the thin-walled component. As the result, the evolution of the residual stresses and the deformation of the final component is controlled. Finally, 3 deformation validation experiments are carried out to process the same thin plates, and the deformation of the thin plates are compared. The experimental results indicate that the maximum deformation can be reduced by 82.2%.
Zhongxi ZHANG , Shuaiqin WANG , Huijuan ZHAO , Dinghua ZHANG , Longhao WANG . Residual stresses evolution mechanism of thin⁃walled component and deformation control method[J]. ACTA AERONAUTICAET ASTRONAUTICA SINICA, 2024 , 45(13) : 629365 -629365 . DOI: 10.7527/S1000-6893.2023.29365
1 | LUO M, LUO H, ZHANG D H, et al. Improving tool life in multi-axis milling of Ni-based superalloy with ball-end cutter based on the active cutting edge shift strategy[J]. Journal of Materials Processing Technology, 2018, 252: 105-115. |
2 | MALI R A, GUPTA T V K, RAMKUMAR J. A comprehensive review of free-form surface milling-Advances over a decade[J]. Journal of Manufacturing Processes, 2021, 62: 132-167. |
3 | 张吉银, 姚倡锋, 谭靓, 等. 喷丸强化残余应力对疲劳性能和变形控制影响研究进展[J]. 机械工程学报, 2023, 59(6): 46-60. |
ZHANG J Y, YAO C F, TAN L, et al. Research progress of the effect of shot peening residual stress on fatigue performance and deformation control[J]. Journal of Mechanical Engineering, 2023, 59(6): 46-60 (in Chinese). | |
4 | 岳彩旭, 张俊涛, 刘献礼, 等. 薄壁件铣削过程加工变形研究进展[J]. 航空学报, 2022, 43(4): 525164. |
YUE C X, ZHANG J T, LIU X L, et al. Research progress on machining deformation of thin-walled parts in milling process[J]. Acta Aeronautica et Astronautica Sinica, 2022, 43(4): 525164 (in Chinese). | |
5 | ZHANG Z, LI L, YANG Y, et al. Machining distortion minimization for the manufacturing of aeronautical structure[J]. International Journal of Advanced Manufacturing Technology, 2014, 73(9-12): 1765-1773. |
6 | LUO M, LUO H, AXINTE D, et al. A wireless instrumented milling cutter system with embedded PVDF sensors[J]. Mechanical Systems and Signal Processing, 2018, 110: 556-568. |
7 | LIU C Q, LI Y G, HAO X Z. An adaptive machining approach based on in-process inspection of interim machining states for large-scaled and thin-walled complex parts[J]. International Journal of Advanced Manufacturing Technology, 2017, 90(9-12): 3119-3128. |
8 | XU J T, XU L K, LI Y F, et al. Shape-adaptive CNC milling for complex contours on deformed thin-walled revolution surface parts[J]. Journal of Manufacturing Processes, 2020, 59: 760-771. |
9 | HAO X Z, LI Y G, DENG T C, et al. Tool path transplantation method for adaptive machining of large-sized and thin-walled free form surface parts based on error distribution[J]. Robotics and Computer-Integrated Manufacturing, 2019, 56: 222-232. |
10 | CERUTTI X, MOCELLIN K. Influence of the machining sequence on the residual stress redistribution and machining quality: Analysis and improvement using numerical simulations[J]. International Journal of Advanced Manufacturing Technology, 2016, 83(1-4): 489-503. |
11 | HAO X Z, LI Y G, NI Y, et al. A collaborative optimization method of machining sequence for deformation control of double-sided structural parts[J]. International Journal of Advanced Manufacturing Technology, 2020, 110(11-12): 2941-2953. |
12 | TOUBHANS B, VIPREY F, FROMENTIN G, et al. Study of phenomena responsible for part distortions when turning thin Inconel 718 workpieces[J]. Journal of Manufacturing Processes, 2021, 61: 46-55. |
13 | LI B Z, JIANG X H, YANG J G, et al. Effects of depth of cut on the redistribution of residual stress and distortion during the milling of thin-walled part[J]. Journal of Materials Processing Technology, 2015, 216: 223-233. |
14 | HUANG K, YANG W, YE X. Adjustment of machining-induced residual stress based on parameter inversion[J]. International Journal of Mechanical Sciences, 2018, 135: 43-52. |
15 | 吴宝海, 郑志阳, 张阳, 等. 面向薄壁零件加工变形与振动控制的智能装夹技术研究进展[J]. 机械工程学报, 2021, 57(17): 21-34. |
WU B H, ZHENG Z Y, ZHANG Y, et al. Intelligent clamping technology for machining deformation and vibration control of thin-wall parts: a review of recent progress[J]. Journal of Mechanical Engineering, 2021, 57(17): 21-34 (in Chinese). | |
16 | 郑志阳, 张阳, 张钊, 等. 基于GA?SVR的薄壁叶片辅助支撑布局优化方法[J]. 航空学报, 2023, 44(4): 426805. |
ZHENG Z Y, ZHANG Y, ZHANG Z, et al. Layout optimization of auxiliary support for thin-walled blade based on GA-SVR[J]. Acta Aeronautica et Astronautica Sinica, 2023, 44(4): 426805 (in Chinese). | |
17 | XING Y F. Fixture layout design of sheet metal parts based on global optimization algorithms[J]. Journal of Manufacturing Science and Engineering, Transactions of the ASME, 2017, 139(10): 1-10. |
18 | RAMACHANDRAN T, SURENDARNATH S, DHARMALINGAM R. Engine-bracket drilling fixture layout optimization for minimizing the workpiece deformation[J]. Engineering Computations (Swansea, Wales), 2020, 38(5): 1978-2002. |
19 | YU J H, CHEN Z T, JIANG Z P. A control process for machining distortion by using an adaptive dual-sphere fixture[J]. International Journal of Advanced Manufacturing Technology, 2016, 12: 3463-3470. |
20 | HAO Q L, YANG Q. A self-adaptive auxiliary fixture for deformation control in blade machining[J]. International Journal of Advanced Manufacturing Technology, 2020, 111(5-6): 1415-1423. |
21 | GONZALO O, SEARA J M, GURUCETA E, et al. A method to minimize the workpiece deformation using a concept of intelligent fixture[J]. Robotics and Computer-Integrated Manufacturing, 2017, 48: 209-218. |
22 | HAO X Z, LI Y G, CHEN G X, et al. 6+X locating principle based on dynamic mass centers of structural parts machined by responsive fixtures[J]. International Journal of Machine Tools and Manufacture, 2018, 125: 112-122. |
23 | CHATELAIN J F, LALONDE J F, TAHAN A S. Effect of residual stresses embedded within workpieces on the distortion of parts after machining[J]. International Journal of Mechanics, 2012, 6(1): 43-51. |
24 | HAO X Z, LI Y G, LI M Q, et al. A part deformation control method via active pre-deformation based on online monitoring data[J]. International Journal of Advanced Manufacturing Technology, 2019, 104(5-8): 2681-2692. |
25 | ZHANG Z X, LUO M, TANG K, et al. A new in-processes active control method for reducing the residual stresses induced deformation of thin-walled parts[J]. Journal of Manufacturing Processes, 2020, 59: 316-325. |
26 | GAMEROS A, LOWTH S, AXINTE D, et al. State-of-the-art in fixture systems for the manufacture and assembly of rigid components: A review[J] International Journal of Machine Tools and Manufacture, 2017,123: 1-21. |
27 | ZHANG Z X, ZHANG Z, ZHANG D H, et al. Milling distortion prediction for thin-walled component based on the average MIRS in specimen machining[J]. International Journal of Advanced Manufacturing Technology, 2020, 111(11-12): 3379-3392. |
/
〈 |
|
〉 |