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Research on adaptive CNC machining arithmetic and process for near-net-shaped jet engine blade

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Abstract

Near-net-shaped jet engine blade machining process have better performance on both reducing material waste during production and improving work reliability in service, while precision machining of this blade is very challengeable and difficult due to its positioning difficulty and low stiffness. This paper propose that reasonable fixture and adaptive CNC machining technology can provide a systematic solution for the machining of near-net-shaped blade Tenon root, tip and Leading edges and Trailing edges (LTE). Firstly, process characteristics, difficulties and requirements of near-net-shaped blade are analyzed. Secondly, adaptive CNC machining process and its key technical principles are introduced and optimized, and proposes measuring bad points culling algorithm of simultaneously using distance relationship, angle relationship and radius relationship, and proposes camber line calculation algorithm of equidistant offset, and optimizes the iterative closest point (ICP) algorithm based on point-to-line ICP algorithm with six control points, and realizes the reconstruction of processing model. Finally, the feasibility of the proposed adaptive CNC machining process and the designed Polyetheretherketone (PEEK-GF30) material and multi-points support rigid-flexible coupling fixture are verified by a typical near-net-shaped blade LTE and Tenon root adaptive CNC machining process experiments. The results shows that the proposed process scheme of reasonable fixture and adaptive CNC machining process can solve two problems of near-net-shaped blade manufacturing of position difficulty and low stiffness. The designed fixture of PEEK-GF30 material and multi-point support rigid-flexible coupling, and the optimized adaptive CNC machining process algorithms can realize high-precision manufacturing of near-net-shaped jet engine blade.

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References

  • Ahmed, E., Soumaya, Y., Mohamed-Salah, O., & Yasser, S. (2019). Failure time prediction using adaptive logical analysis of survival curves and multiple machining signals. Journal of Intelligent Manufacturing. https://doi.org/10.1007/s10845-018-1453-4.

    Article  Google Scholar 

  • Alexa, M., Coheror, D., & Levin, D. (2002). As rigid as possible shape interpolation. Computer Graphics,34(1), 157–164.

    Google Scholar 

  • Besl, P. J., & Mclay, N. D. (1992). A method for registration of 3D shapes. IEEE Transactions on Pattern Analysis Machine Intelligence,14(2), 239–256.

    Article  Google Scholar 

  • Bradley, G., & Vickers, G. W. (2002). Automated rapid prototyping utilizing laser scanning and free machining. Annals of CIRP,41, 437–440.

    Article  Google Scholar 

  • Chatelain, J. F. (2005). A level-based optimization algorithm for complexpart localization. Precision Engineering,29(2), 197–207.

    Article  Google Scholar 

  • Elamaraghy, H., Bararia, A., & Knopf, G. K. (2004). Integrated inspection and machining for maximum conformance to design tolerances. CIRP Annals - Manufacturing Technology,53(1), 411–416.

    Article  Google Scholar 

  • Gao, J., Chen, X., Yilmaz, O., & Gindy, N. (2008a). An integrated adaptive repair solution for complex aerospace components through geometry reconstruction. The International Journal of Advanced Manufacturing Technology,36, 1170–1179.

    Article  Google Scholar 

  • Gao, J., Chen, X., Zhang, D. T., & Nabil, G. (2008b). Adaptive repair approach for recovering components from defects. Chinese Journal of Mechanical Engineering,21(1), 57–60.

    Article  Google Scholar 

  • Hebert, M., & Jairo, E. (2007). A regularization approach for surface reconstruction from point clouds. Applied Mathematics and Computation,188(1), 583–595.

    Article  Google Scholar 

  • Hugues, H., Tony, D. R., & Tom, D. (1992). Surface reconstruction from unorganized points. ACM Siggraph Computer Graphics,26(2), 71–78.

    Article  Google Scholar 

  • Kamran, J., Rafael, G., Xiang, Li, & Noureddine, Z. (2018). Tool wear monitoring and prognostics challenges: A comparison of connectionist methods toward an adaptive ensemble model. Journal of Intelligent Manufacturing,29, 1873–1890.

    Article  Google Scholar 

  • Katz, R., Srivatsan, V., & Patil, L. (2011). Closed-loop machining cell for turbine blades. The International Journal of Advanced Manufacturing Technology,55, 869–881.

    Article  Google Scholar 

  • Ko, K. H., Maekawa, T., & Patrikala, N. M. (2003a). An algorithm for optimal free-form object matching. Computer-Aided Design,35(10), 913–923.

    Article  Google Scholar 

  • Ko, K. H., Maekawa, T., & Patrikala, N. M. (2003b). Shape intrinsic properties for free-form object matching. Journal of Computing and Information Science in Engineering,3(4), 325–333.

    Article  Google Scholar 

  • Li, Y. D., & Gu, P. H. (2003). Free-form surface inspection techniques state of the art review. Computer-Aided Design,36(13), 1395–1417.

    Article  Google Scholar 

  • Lin, X. J., Wu, D., Yang, B., Wu, G., Shan, X., Xiao, Q., et al. (2017). Research on the mechanism of milling surface waviness formation in thin-walled blades. The International Journal of Advanced Manufacturing Technology,93, 2459–2470.

    Article  Google Scholar 

  • Marini, D., Cunningham, D., & Corney, J. R. (2018). Near net shape manufacturing of metal: A review of approaches and their evolutions. Proceedings of the Institution of Mechanical Engineers, Part B: J Engineering Manufacture,232, 650–669.

    Article  Google Scholar 

  • Mears, L., Roth, J. T., & Djurdjanovic, D. (2008). Quality and inspection of machining inperations: CMM integration to the machine tool. Journal of Manufacturing Science and Engineering,131(5), 051006–051013.

    Article  Google Scholar 

  • Mohaghegh, K., Sadeghi, M. H., & Abdullah, A. (2007). Reverse engineering of turbine blades based on design intent. Original Article,32, 1009–1020.

    Google Scholar 

  • Sunil, S., & Nandihalli (2004). A B-spline geometric modeling methodology for free surface simulations. Mississippi: Mississippi State University.

    Google Scholar 

  • Ren, J., Feng, Y., Mi, X., & Xu, Y. (2015). Adaptive CNC machining technology for precision forging blades of aeroengines. Aeronautical Manufacturing Technology,22, 52–55+59.

    Google Scholar 

  • Sharp, G. G., Lee, S. W., & Wehe, D. K. (2002). ICP registration using invariant features. IEEE Transactions on Pattern Analysis Machine Intelligence,24(1), 90–102.

    Article  Google Scholar 

  • Somkiat, T. (2011). Advance in detection system to improve the stability and capability of CNC turning process. Journal of Intelligent Manufacturing,22, 843–852.

    Article  Google Scholar 

  • Sun, Y. W., Ming, W. X., Guo, D. M., & Liu, J. (2009a). Machining localization and quality evaluation of parts with sculptured surfaces using SQP method. International Journal of Advanced Manufacturing Technology,42(11), 1131–1139.

    Google Scholar 

  • Sun, Y. W., Xu, J. T., Guo, D. M., & Jia, Z. Y. (2009b). A unified localization approach for machining allowance optimization of complex curved surfaces. Precision Engineering,33(4), 516–523.

    Article  Google Scholar 

  • Wu, X. M., & Li, G. X. (2009) A new surface reconstruction method in reverse engineering (pp. 334–338). IEEE.

  • Xiong, Z. H., Wang, M. Y., & Li, Z. X. (2003). A computer-aided probing strategy for workpiece localization. IEEE International Conference on Robotics & Automation,3(1), 3941–3946.

    Google Scholar 

  • Xiong, Z., Wang, M. Y., & Li, Z. (2004). A near-optimal probing strategy for workpiece localization. IEEE Transactions on Robotics,20(4), 668–676.

    Article  Google Scholar 

  • Xu, J. T., Wei, J. L., & Yu, W. S. (2007). Free surface matching algorithm based on curvature feature. Journal of Computer-Aided Design & Computer Graphics,19(2), 193–197.

    Google Scholar 

  • Yi, X., Ma, L. M., & Li, Z. X. (2008). A geometric algorithm for symmetric workpiece localization. In Proceedings of the 7th World Congress on Intelligent Control and Automation, Chongqing, China (pp. 6025–6029).

  • Zhang, Z., Zhang, D., Luo, M., & Wu, B. (2016). Research of machining vibration restraint method for compressor blade. Procedia CIRP,56, 133–136.

    Article  Google Scholar 

  • Zuper, U., Cus, F., & Reibenschuh, M. (2012). Modeling and adaptive force control of milling by using artificial techniques. Journal of Intelligent Manufacturing,23, 1805–1815.

    Article  Google Scholar 

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Acknowledgements

The author would like to acknowledge the support and contributions of our colleagues in Xi’an Aero-Engine (Group) Ltd. This research is supported in part by Xi’an Aero-Engine (Group) Ltd., National Key Scientific Instrument and Equipment Development Project (2016YFF0101900), National Natural Science Foundation of China (Grant 51575310) and Beijing Municipal Natural Science Foundation (Grant 3162014).

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Correspondence to Hui Wang.

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Wu, D., Wang, H., Zhang, K. et al. Research on adaptive CNC machining arithmetic and process for near-net-shaped jet engine blade. J Intell Manuf 31, 717–744 (2020). https://doi.org/10.1007/s10845-019-01474-z

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