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Vibration suppression in macro–micro grinding system of aeroengine blade based on impedance compensation prediction control strategy

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Abstract

In the process of aeroengine blade grinding, the vibration of the robot reduces the precision of grinding force control at the end, which seriously affects the processing quality of the blade. Thus, a macro–micro grinding system composed of a robot and a pneumatic end-effector is constructed. The system is controlled by the robot to realize the position and the end-effector to realize the force control. Based on a simplified model of the robot and the end-effector, a force compensation strategy combining a dynamic matrix prediction algorithm and an impedance compensation method is proposed. The axial grinding force and vibration compensation force are rolling optimized in a limited time domain in a way of minimizing the quadratic performance index, the time lag of the force compensation process and the uncertainty of model parameters are compensated, and the grinding force can be tracked stably is realized. The simulation and experimental results indicate that the method can quickly suppress the vibration, decrease the force fluctuation, and improve the blade grinding quality.

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Available on request.

Code availability

The codes that support the findings of this study are available from the corresponding author upon reasonable request.

References

  1. Xiao GJ, Chen BQ, Li CS, Zhuo XQ (2022) Fatigue life analysis of aero-engine blades for abrasive belt grinding considering residual stress. Eng Fail Anal 131:105846. https://doi.org/10.1016/j.engfailanal.2021.105846

    Article  Google Scholar 

  2. Chen ZS, Sheng HS, Xia YM, Wang WM, He J (2021) A comprehensive review on blade tip timing-based health monitoring: status and future. Mech Syst Signal Process 149:107330. https://doi.org/10.1016/j.ymssp.2020.107330

    Article  Google Scholar 

  3. Zhu DH, Xu XH, Jiang C, Li WL (2021) Research progress of robot grinding and polishing technology for complex blades. Acta Aeronaut Astronaut Sin 42:8–30. https://doi.org/10.7527/S1000-6893.2020.242

    Article  Google Scholar 

  4. Zhu DH, Feng XZ, Xu XH, Yang ZY, Li WL, Yan SJ, Ding H (2020) Robotic grinding of complex components: a step towards efficient and intelligent machining-challenges, solutions, and applications. Robot Comput-Integr Manuf 65:101908. https://doi.org/10.1016/j.rcim.2019.101908

    Article  Google Scholar 

  5. Kakinuma Y, Ogawa S, Koto K (2022) Robot polishing control with an active end effector based on macro-micro mechanism and the extended Preston’s law. CIRP Ann Manuf Technol 71:341–344. https://doi.org/10.1016/j.cirp.2022.04.074

    Article  Google Scholar 

  6. Li J, Guan YS, Chen HW, Wang B, Zhang T (2020) A high-bandwidth end-effector with active force control for robotic polishing. IEEE Access 8:122–135. https://doi.org/10.1109/access.2020.3022930

    Article  Google Scholar 

  7. Wei YZ, Xu QS (2022) Design of a new passive end-effector based on constant-force mechanism for robotic polishing. Robot Comput-Integr Manuf 74:102278. https://doi.org/10.1016/j.rcim.2021.102278

    Article  Google Scholar 

  8. Dai SJ, Li SN, Ji WB, Sun ZL, Zhao YF (2021) Force tracking control of grinding end effector based on backstepping+ PID. Ind Rob 49:34–46. https://doi.org/10.1108/IR-10-2020-0229

    Article  Google Scholar 

  9. Zhang GL, Yang GL, Deng YM, Chen CY, Zhu RF, Yang KS (2022) Modeling and force control of a pneumoelectric end-effector for robotic continuous contact operations. Int J Adv Manuf Technol 121:1219–1234. https://doi.org/10.1007/s00170-022-09413-8

    Article  Google Scholar 

  10. Tao B, Zhao XW, Li RP, Ding H (2020) Research and application of robot measurement operation machining integration technology. China Mech Eng 31:49–56. https://doi.org/10.396/j.issn.1004-132X.2020.01.006

  11. Pervez MR, Ahamed MH, Ahmed MA, Takrim SM, Dario P (2022) Autonomous grinding algorithms with future prospect towards SMART manufacturing: a comparative survey. J Manuf Syst 62:164–185. https://doi.org/10.1016/j.jmsy.2021.11.009

    Article  Google Scholar 

  12. Furtado LFF, Villani E, Trabasso LG, Sutério R (2017) A method to improve the use of 6-dof robots as machine tools. Int J Adv Manuf Technol 92:2487–2502. https://doi.org/10.1007/s00170-017-0336-8

    Article  Google Scholar 

  13. Newman M, Lu KY, Khoshdarregi M (2021) Suppression of robot vibrations using input shaping and learning-based structural models. J Intell Mater Syst Struct 32:1001–1012. https://doi.org/10.1177/1045389X20947166

    Article  Google Scholar 

  14. Nguyen V, Cvitanic T, Melkote S (2019) Data-driven modeling of the modal properties of a six-degrees-of-freedom industrial robot and its application to robotic milling. J Manuf Sci Eng 141(12):121006. https://doi.org/10.1115/1.4045175

    Article  Google Scholar 

  15. Nguyen V, Johnson J, Melkote S (2020) Active vibration suppression in robotic milling using optimal control. Int J Adv Manuf Technol 152:103541. https://doi.org/10.1016/j.ijmachtools.2020.103541

    Article  Google Scholar 

  16. Mohammad AEK, Hong J, Wang D (2018) Design of a force-controlled end-effector with low-inertia effect for robotic polishing using macro-mini robot approach. Robot Comput-Integr Manuf 49:54–65. https://doi.org/10.1016/j.rcim.2017.05.011

    Article  Google Scholar 

  17. Ivanov V, Botko F, Dehtiarov I, Kočiško M, Evtuhov A, Pavlenko I, Trojanowska J (2022) Development of flexible fixtures with incomplete locating: connecting rods machining case study. Machines 10(7):493. https://doi.org/10.3390/machines10070493

    Article  Google Scholar 

  18. Bao Y, Wang B, He ZX, Kang RK, Guo J (2022) Recent progress in flexible supporting technology for aerospace thin-walled parts: a review. Chin J Aeronaut 35:10–26. https://doi.org/10.1016/j.cja.2021.01.026

    Article  Google Scholar 

  19. Jiang X, Zhao G, Lu W (2020) Vibration suppression of complex thin-walled workpiece based on magnetorheological fixture. J Manuf Syst 106:1043–1055. https://doi.org/10.1007/s00170-019-04612-2

    Article  Google Scholar 

  20. Wojciechowski S, Maruda RW, Krolczyk GM, Niesłony P (2018) Application of signal to noise ratio and grey relational analysis to minimize forces and vibrations during precise ball end milling. Precis Eng 51:582–596. https://doi.org/10.1016/j.precisioneng.2017.10.014

    Article  Google Scholar 

  21. Wang Q, Wang W, Zheng L, Yun C (2021) Force control-based vibration suppression in robotic grinding of large thin-wall shells. Robot Comput-Integr Manuf 67:102031. https://doi.org/10.1016/j.rcim.2020.102031

    Article  Google Scholar 

  22. Cheng MD, Guo JJ, Li Z, Li GM (2018) Vibration suppression for thin-wall plate machining using eddy-current damping. J Mech Eng 17:76–84. https://doi.org/10.3901/JME.2018.17.076

    Article  Google Scholar 

  23. Yuan X, Wang S, Mao X, Liu H, Liang Z, Guo Q, Yan R (2022) Forced vibration mechanism and suppression method for thin-walled workpiece milling. Int J Mech Sci 230:107553. https://doi.org/10.1016/j.ijmecsci.2022.107553

    Article  Google Scholar 

  24. Chen F, Zhao H, Li D, Chen L, Tan C, Ding H (2019) Contact force control and vibration suppression in robotic polishing with a smart end effector. Robot Comput-Integr Manuf 57:391–403. https://doi.org/10.1016/j.rcim.2018.12.019

    Article  Google Scholar 

  25. Zhou P, Zhao X, Tao B, Ding H (2020) Time-varying isobaric surface reconstruction and path planning for robotic grinding of weak-stiffness workpieces. Robot Comput-Integr Manuf 64:101945. https://doi.org/10.1016/j.rcim.2020.101945

    Article  Google Scholar 

  26. Yang Z, Chen C, Chen W, Chen H, Liu Z (2022) Improved sliding mode dynamic matrix control strategy: application on spindle loading and precision measuring device based on piezoelectric actuator. Mech Syst Signal Process 167:1–19. https://doi.org/10.1016/j.ymssp.2021.108543

    Article  Google Scholar 

  27. Guo X, Li C, Luo Z, Cao D (2021) Modal parameter identification of structures using reconstructed displacements and stochastic subspace identification. Appl Sci 11(23):11432. https://doi.org/10.3390/app112311432

    Article  Google Scholar 

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Funding

This work is jointly funded by the National Key Research and Development Program of China (Grant number 2019YFB1311104) and the China Natural Science Foundation (Grant number 52005154).

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All authors contributed to the study conception and design. Shijie Dai: resources and validation; Shuyuan Liu: conceptualization, methodology, and writing—original draft; Wenbin Ji: writing—review and editing; Shida Li: investigation and supervision. All authors read and approved the final manuscript.

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Correspondence to Wenbin Ji.

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Dai, S., Liu, S., Ji, W. et al. Vibration suppression in macro–micro grinding system of aeroengine blade based on impedance compensation prediction control strategy. Int J Adv Manuf Technol 125, 793–807 (2023). https://doi.org/10.1007/s00170-022-10721-2

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