2023, Volume 22, Issue 3
Engineering >> 2023, Volume 22, Issue 3 doi: 10.1016/j.eng.2022.07.018
A New Method for Inferencing and Representing a Workpiece Residual Stress Field Using Monitored Deformation Force Data
a College of Mechanical and Electrical Engineering, Nanjing University of Aeronautics and Astronautics, Nanjing 210016, China
b School of Engineering, University of Greenwich, Chatham Maritime ME4 4TB, UK
# These authors contributed equally to this work.
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Abstract
The residual stress inside stock materials is a fundamental property related to the quality of manufactured parts in terms of geometric/dimensional stability and fatigue life. For large parts that must meet high-precision requirements, accurately measuring and predicting the residual stress field has been a major challenge. Existing technologies for measuring the residual stress field are either strain-based measurement methods or non-destructive methods with low efficiency and accuracy. This paper reports a new non-destructive method for inferencing the residual stress field based on deformation forces. In the proposed method, the residual stress field of a workpiece is inferred based on the characteristics of the deformation forces that reflect the overall effect of the unbalanced residual stress field after material removal operations. The relationship between deformation forces and the residual stress field is modeled based on the principle of virtual work, and the residual stress field inference problem is solved using an enforced regularization method. Theoretical verification is presented and actual experiment cases are tested, showing reliable accuracy and flexibility for large aviation structural parts. The underlying principle of the method provides an important reference for predicting and compensating workpiece deformation caused by residual stress using dynamic machining monitoring data in the context of digital and intelligent manufacturing.
Keywords
Residual stress field ; Precision manufacturing ; Deformation force ; Inverse problem ; In situ ; measurement
SupplementaryMaterials
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References
[ 1 ] Geeenough GB. Internal stresses in metals. Nature 1948;161(4096):683. link1
[ 2 ] Wang YM, Voisin T, McKeown JT, Ye J, Calta NP, Li Z, et al. Additively manufactured hierarchical stainless steels with high strength and ductility. Nat Mater 2018;17(1):63–71. link1
[ 3 ] Xu Y, Joseph S, Karamched P, Fox K, Rugg D, Dunne FPE, et al. Predicting dwell fatigue life in titanium alloys using modelling and experiment. Nat Commun 2020;11(1):5868. link1
[ 4 ] Li Y, Shi Z, Lin J, Yang YL, Saillard P, Said R. Effect of machining-induced residual stress on springback of creep age formed AA2050 plates with asymmetric creep-ageing behaviour. Int J Mach Tools Manuf 2018;132: 113–22. link1
[ 5 ] Yuan S. Fundamentals and processes of fluid pressure forming technology for complex thin-walled components. Engineering 2021;7(3):358–66. link1
[ 6 ] Lu Y, Sun G, Xiao X, Mazumder J. Online stress measurement during laseraided metallic additive manufacturing. Sci Rep 2019;9:7630. link1
[ 7 ] Withers PJ, Bhadeshia HKDH. Residual stress. Part 1—measurement techniques. Mater Sci Technol 2001;17(4):355–65. link1
[ 8 ] Prime MB, Hill MR. Residual stress, stress relief, and inhomogeneity in aluminum plate. Scr Mater 2002;46(1):77–82. link1
[ 9 ] Prime MB. Cross-sectional mapping of residual stresses by measuring the surface contour after a cut. J Eng Mater Technol 2001;123(2):162–8. link1
[10] Treuting RG, Read WT. A mechanical determination of biaxial residual stress in sheet materials. J Appl Phys 1951;22(2):130–4. link1
[11] Wong AK, Dunn SA, Sparrow JG. Residual stress measurement by means of the thermoelastic effect. Nature 1988;332(6165):613–5. link1
[12] Lu L, Dao M, Kumar P, Ramamurty U, Karniadakis GE, Suresh S. Extraction of mechanical properties of materials through deep learning from instrumented indentation. Proc Natl Acad Sci USA 2020;117(13):7052–62. link1
[13] Kirchlechner C, Martinschitz KJ, Daniel R, Mitterer C, Donges J, Rothkirch A, et al. X-ray diffraction analysis of three-dimensional residual stress fields reveals origins of thermal fatigue in uncoated and coated steel. Scr Mater 2010;62(10):774–7. link1
[14] Fratini L, Zuccarello B. An analysis of through-thickness residual stresses in aluminium FSW butt joints. Int J Mach Tools Manuf 2006;46(6):611–9. link1
[15] Shen X, Zhang D, Yao C, Tan L, Yao H. Formation mechanism of surface metamorphic layer and influence rule on milling TC17 titanium alloy. Int J Adv Manuf Technol 2021;112(7–8):2259–76. link1
[16] Zhang Y, Chen S, Cai Y, Lu L, Fan D, Shi J, et al. Novel X-ray and optical diagnostics for studying energetic materials: a review. Engineering 2020;6(9): 992–1005. link1
[17] Jiang W, Woo W, An GB, Park JU. Neutron diffraction and finite element modeling to study the weld residual stress relaxation induced by cutting. Mater Des 2013;51:415–20. link1
[18] Singh DRP, Deng X, Chawla N, Bai J, Hubbard C, Tang G, et al. Residual stress characterization of Al/SiC nanoscale multilayers using X-ray synchrotron radiation. Thin Solid Films 2010;519(2):759–65. link1
[19] Chen H, Wang XL. China’s first pulsed neutron source. Nat Mater 2016;15(7): 689–91. link1
[20] Spradlin TJ, Olson MD. Comparison of residual stress measurements from multiple techniques in die-forged 7085-T7452. In: Proceedings of the 2017 Residual Stress Summit; 2017 Oct 23–26; Dayton, OH, USA. 2017. p. 1–32.
[21] Schajer GS, editor. Practical residual stress measurement methods. Wiley; 2013. link1
[22] Zhao Z, Li Y, Liu C, Liu X. Predicting part deformation based on deformation force data using physics-informed latent variable model. Robot Comput Integr Manuf 2021;72:102204. link1
[23] Cerutti X, Mocellin K. Influence of the machining sequence on the residual stress redistribution and machining quality: analysis and improvement using numerical simulations. Int J Adv Manuf Technol 2016;83(1–4):489–503. link1
[24] Hao X, Li Y, Chen G, Liu C. 6+X locating principle based on dynamic mass centers of structural parts machined by responsive fixtures. Int J Mach Tools Manuf 2018;125:112–22. link1
[25] Li Y, Liu C, Hao X, Gao JX,Maropoulos PG. Responsive fixture design using dynamic product inspection and monitoring technologies for the precision machining of large-scale aerospace parts. CIRP Ann Manuf Technol 2015;64(1):173–6. link1
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