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2000
Volume 19, Issue 7
  • ISSN: 1872-2121
  • E-ISSN: 2212-4047

Abstract

Background

The method was proposed to optimize the warpage and volume shrinkage of the blade of a plant protection unmanned aerial vehicle (UAV) during injection molding. The influence of molding defects on the geometric parameters of airfoil was analyzed from two aspects of blade geometry structure and molding process based on blade element theory. This paper focuses on reducing the warpage and volume shrinkage of the blade in the production process and improving molding quality through moldflow analysis and calculation.

Objective

The purpose of this patent study was to combine injection molding CAE with orthogonal test and response surface method to reduce product warpage and volume shrinkage, improve dimensional accuracy and production efficiency, and combine fluid dynamics simulation experiments to prove the experiment's reliability.

Methodology

The optimization method of injection molding process parameters was proposed based on the orthogonal test and response surface method, combining the principles of aerodynamics mathematics and polymer injection molding. The Taguchi experiment was designed with melt temperature injection time and mold temperature pressure holding time as the optimization variable. The Box-Behnken Design (BBD) experiment was designed, and the response surface model was established with Design-Expert software to analyze the mapping relationship between process parameters and warpage and volume shrinkage. Moldflow software was used for flow analysis on the basis of analysis by response surface method, and the deformed parts were analyzed by computational fluid dynamics (CFD) with ANSYS software to prove the reliability of the calculation process.

Results

The warpage and volume shrinkage of the product can be significantly reduced based on the orthogonal test and response surface model. The aerodynamic performance of the blade can be improved by optimization injection molding, making the actual production of the blade close to the original design blade model to the greatest extent and reducing the actual production trial and error cost.

Conclusion

An optimization method of the injection molding process of the UAV rotor was proposed based on the response surface method and blade element theory. Through the systematic design and optimization of injection molding parameters, the molding quality and performance of the rotor can be improved, which provides a new way to optimize the dynamic components of mass-produced UAVs.

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2024-12-04
2025-07-04
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References

  1. ChangL.S. ZhangQ.Y. GuoX.Y. Airfoil optimization design based on Gaussian process regression and genetic algorithm.Chinese J. Aerospace Power2020362306231610.13224/j.cnki.jasp.20200402
    [Google Scholar]
  2. CruzattyC. SarmientoE. ValenciaE. CandoE. Design methodology of a UAV propeller implemented in monitoring activities.Mater. Today Proc.20224911512110.1016/j.matpr.2021.07.481
    [Google Scholar]
  3. ZangY. HeX.G. ZhouZ.Y. Comprehensive evaluation method for lifting characteristics of electric multi-rotor UAV for plant protection.Nongye Gongcheng Xuebao201834697710.11975/j.issn.1002‑6819.2018.14.009
    [Google Scholar]
  4. YangX. MaD. ZhangL. YuY. YaoY. YangM. High-fidelity multi-level efficiency optimization of propeller for high altitude long endurance UAV.Aerosp. Sci. Technol.202313310814210.1016/j.ast.2023.108142
    [Google Scholar]
  5. ChenX. XuH.Q. Xiao.S.H. Method, system, equipment and medium for transportation supervision of fan blade.China patent, 202210674915.5.
    [Google Scholar]
  6. LeeH.M. RyuJ.K. AhnS.J. Aerodynamic design optimization of uav rotor blades using a genetic algorithm and artificial neural networksJ. Comput. Fluids Eng.2014193293610.6112/kscfe.2014.19.3.029
    [Google Scholar]
  7. XiangS. ZhaoL. ChenH.L. A design method for unmanned aerial vehicle rotor.Chinese Aeronaut.Sci. Technol.20223316
    [Google Scholar]
  8. TadrosM. VenturaM. Guedes SoaresC. Design of propeller series optimizing fuel consumption and propeller efficiency.J. Mar. Sci. Eng.2021911122610.3390/jmse9111226
    [Google Scholar]
  9. WuX. ZuoZ. MaL. ZhangW. Multi-fidelity neural network-based aerodynamic optimization framework for propeller design in electric aircraft.Aerosp. Sci. Technol.202414610896310.1016/j.ast.2024.108963
    [Google Scholar]
  10. LarrabeeE.E. Practical design of minimum induced loss propellers.SAE Trans., vol.19792053206210.4271/790585
    [Google Scholar]
  11. AdkinsC.N. LiebeckR.H. Design of optimum propellers.J. Propuls. Power199410567668210.2514/3.23779
    [Google Scholar]
  12. SongM.C. LiuZ. WangM.J. YuT.M. ZhaoD.Y. Research on effects of injection process parameters on the molding process for ultra-thin wall plastic parts.J. Mater. Process. Technol.2007187-18866867110.1016/j.jmatprotec.2006.11.103
    [Google Scholar]
  13. MohanM. AnsariM.N.M. ShanksR.A. Review on the effects of process parameters on strength, shrinkage, and warpage of injection molding plastic component.Polym. Plast. Technol. Eng.201756111210.1080/03602559.2015.1132466
    [Google Scholar]
  14. WangQ. ZhangJ.P. WangX.W. Deformation pre-compensation of injection molded thin-walled parts based on complex method.Jisuanji Jicheng Zhizao Xitong20232936923703
    [Google Scholar]
  15. KashyapS. DattaD. Process parameter optimization of plastic injection molding: a review.Int. J. Plas. Tech.201519111810.1007/s12588‑015‑9115‑2
    [Google Scholar]
  16. WuC.H. LiangW.J. Effects of geometry and injection-molding parameters on weld-line strength.Polym. Eng. Sci.20054571021103010.1002/pen.20369
    [Google Scholar]
  17. LiuL. CaoC. LV, Q.Y. “Analysis and Optimization of Forming Precision of Axial Fan Blade Based on DOE and RSM”.Materials Reports20223626226610.11896/cldb.20090121
    [Google Scholar]
  18. JaiganeshV. ManivannanS. ManivannanS. Numerical analysis and simulation of nylon composite propeller for aircraft.Procedia Eng.2014971079108810.1016/j.proeng.2014.12.386
    [Google Scholar]
  19. RutkayB. LalibertéJ. Design and manufacture of propellers for small unmanned aerial vehicles.J. Unmanned Veh. Syst.20164422824510.1139/juvs‑2014‑0019
    [Google Scholar]
  20. ZhangW.G. SunJ.F. ZhaoQ.J. Aerodynamic design and verification methods of rotor airfoilsActa Aerodyn. Sini.202139613614810.7638/kqdlxxb‑2021.0315
    [Google Scholar]
  21. KovačevićA. SvorcanJ. HasanM.S. IvanovT. JovanovićM. Optimal propeller blade design, computation, manufacturing and experimental testing.Aircr. Eng. Aerosp. Technol.20219381323133210.1108/AEAT‑03‑2021‑0091
    [Google Scholar]
  22. RostamiM. FarajollahiA. Aerodynamic performance of mutual interaction tandem propellers with ducted UAV.Aerosp. Sci. Technol.202110810639910.1016/j.ast.2020.106399
    [Google Scholar]
  23. ZhuH. JiangZ. ZhaoH. PeiS. LiH. LanY. Aerodynamic performance of propellers for multirotor unmanned aerial vehicles: Measurement, analysis, and experiment.Shock Vib.2021202111110.1155/2021/9538647
    [Google Scholar]
  24. NingA. Using blade element momentum methods with gradient-based design optimization.Struct. Multidiscipl. Optim.2021642991101410.1007/s00158‑021‑02883‑6
    [Google Scholar]
  25. BeniniE. ToffoloA. Optimal design of horizontal-axis wind turbines using blade-element theory and evolutionary computation.J. Sol. Energy Eng.2002124435736310.1115/1.1510868
    [Google Scholar]
  26. MengK. WuQ. XuJ. ChenW. FengZ. SchoberR. SwindlehurstA.L. UAV-enabled integrated sensing and communication: opportunities and challenges.IEEE Wirel. Commun.20243129710410.1109/MWC.131.2200442
    [Google Scholar]
  27. MengK. WuQ. MaS. ChenW. QuekT.Q.S. UAV trajectory and beamforming optimization for integrated periodic sensing and communication.IEEE Wirel. Commun. Lett.20221161211121510.1109/LWC.2022.3161338
    [Google Scholar]
  28. ChowdaryA. BazziA. ChafiiM. On hybrid radar fusion for integrated sensing and communication.IEEE Trans. Wirel. Commun.2024January1110.1109/TWC.2024.3357573
    [Google Scholar]
  29. BazziA. ChafiiM. On outage-based beamforming design for dual-functional radar-communication 6g systems.IEEE Trans. Wirel. Commun.20232285598561210.1109/TWC.2023.3235617
    [Google Scholar]
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