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Journal of Vibration Testing and System Dynamics 7(4) (2023) 431--445 | DOI:10.5890/JVTSD.2023.12.003

Ze-wen Cui$^{1, 2}$, Zhong Luo$^{1, 2, 3}$, Lei Li${}^{1, 2}$, Kai Sun${}^{1, 2}$, Dong-ze Wu${}^{1, 2}$

${}^{1}$ School of Mechanical Engineering and Automation, Northeastern University, Shenyang 110819, PR China

${}^{2}$ Foshan Graduate School of Northeastern University, Foshan 528312, PR China

${}^{3}$ Key Laboratory of Vibration and Control of Aero-Propulsion System Ministry of Education, Northeastern

University, Shenyang 110819, PR China

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Abstract

Aiming at the problems that the complex rotor system is difficult to carry out and monitor due to variable load and bad working conditions, the design method of software platform based on digital twin technology is studied, and the architecture and main function realization of digital twin software platform are explored from six aspects: physical layer, virtual layer, data layer, functional layer, client layer and connection layer. A method to establish the digital twin model of rotor system integrating geometric model and mechanism model is proposed. The digital twin model of the existing rotor test-bed is constructed. Based on the digital twin software platform of the rotor test-bed, the rationality of the design and implementation method is verified by comparison with the experiment.

References

1. [1]	Grieves, M. (2014), Digital twin: manufacturing excellence through virtual factory replication, White paper, 1, 1-7.

2. [2]	Tao, F., Cheng, J., Qi, Q., Zhang, M., Zhang, H., and Sui, F. (2018), Digital twin-driven product design, manufacturing and service with big data, The International Journal of Advanced Manufacturing Technology, 94(9), 3563-3576.

3. [3]	Tao, F. and Qi, Q. (2019), Make more digital twins, Nature, 573, 490-491.

4. [4]	Enders, M.R. and Ho{\ss}bach, N. (2019), Dimensions of digital twin applications - a literature review, Amcis 2019 Proceedings, 20.

5. [5]	Schleich, B., Anwer, N., Mathieu, L., and Wartzack, S. (2017), Shaping the digital twin for design and production engineering, CIRP Annals, 66(1), 141-144.

6. [6]	Zhang, M., Tao, F., Huang, B., Liu, A., Wang, L., Anwer, N., and Nee, A.Y.C. (2021), Digital twin data: methods and key technologies, Digital Twin, 1(2), 2-10.

7. [7]	Haag, S. and Anderl, R. (2018), Digital twin--proof of concept, Manufacturing Letters, 15, 64-66.

8. [8]	Guivarch, D., Mermoz, E., Marino, Y., and Sartor, M. (2019), Creation of helicopter dynamic systems digital twin using multibody simulations, CIRP Annals, 68(1), 133-136.

9. [9]	Liu, Q., Zhang, H., Leng, J., and Chen, X. (2019), Digital twin-driven rapid individualized designing of automated flow-shop manufacturing system, International Journal of Production Research, 57(12), 3903-3919.

10. [10]	Zhang, H., Qi, Q., and Tao, F. (2022), A multi-scale modeling method for digital twin shop-floor, Journal of Manufacturing Systems, 62, 417-428.

11. [11]	Zheng, M.and Tian, L. (2021), A hierarchical integrated modeling method for the digital twin of mechanical products, Machines, 10(1), p.2.

12. [12]	Lai, X., Wang, S., Guo, Z., Zhang, C., Sun, W., and Song, X. (2021), Designing a shape-performance integrated digital twin based on multiple models and dynamic data: a boom crane example, Journal of Mechanical Design, 143(7), 1-15.

13. [13]	Wang, Y., Tao, F., Zhang, M., Wang, L., and Zuo, Y. (2021), Digital twin enhanced fault prediction for the autoclave with insufficient data, Journal of Manufacturing Systems, 60, 350-359.

14. [14]	Wang, J., Ye, L., Gao, R.X., Li, C., and Zhang, L. (2019), Digital Twin for rotating machinery fault diagnosis in smart manufacturing, International Journal of Production Research, 57(12), 3920-3934.

15. [15]	Bolotov, M. A. Pechenin, V. A. Pechenina, E. J. et al. (2020), Algorithm for predicting the vibrational state of a turbine rotor using machine learning, Aerospace and Mechanical Engineering, 19(1), 18-27.

16. [16]	Bolotov, M.A., Pechenin, V.A., Pechenina, E.J., and Ruzanov, N.V. (2021), Design and application of digital twin system for the blade-rotor test rig, Journal of Intelligent Manufacturing, 2021, 34(2), 753-769.

17. [17]	Chetan, M., Yao, S., and Griffith, D.T. (2021), Multi-fidelity digital twin structural model for a sub-scale downwind wind turbine rotor blade, Wind Energy, 24(12), 1368-1387.

18. [18]	Li, L., Luo, Z., He, F., Sun, K., and Yan, X. (2022), An improved partial similitude method for dynamic characteristic of rotor systems based on Levenberg--Marquardt method, Mechanical Systems and Signal Processing, 165.

19. [19]	Nelson, H.D. (1980), A finite rotating shaft element using timoshenko beam theory, Journal of Mechanical Design, 102, 793-803.

20. [20]	Li, L., Luo, Z., He, F., Zhao, X., and Liu, J. (2020), A partial similitude method considering variable powers in scaling laws and applied to rotor-bearing systems, International Journal of Mechanical Sciences, 186, p.105892.

21. [21]	Li, L., Luo, Z., He, F., Ding, Z., and Sun, K. (2021), A partial similitude method for vibration responses of rotor systems: numerical and experimental verification, International Journal of Mechanical Sciences, 208, p.106696.

22. [22]	Jha, A.K. Dewangan, P., Sarangi, M. (2016), model updating of rotor systems by using nonlinear least square optimization, Journal of Sound and Vibration, 373, 251-262.