A Full-field Sensing Method for Vibration State of Rotating Bladed Disks Driven by Digital Twin

doi:10.3901/JME.2023.21.270

Abstract

Abstract: Aiming at the limitation that the on-line monitoring method of rotating bladed disk can only obtain limited measuring point information, a virtual sensing technology framework of the global vibration state of rotating bladed disk based on the digital twin is proposed. Firstly, the functions and logical relationships of each module in the technical system are introduced from the physical space and digital space by using the digital twin theory, and the technical route to realize the full-field sensing of the rotating bladed disk is described. Secondly, the key technologies and implementation methods of twin model construction, non-contact vibration test, update of twin model, virtual sensing and visual module development are described in detail. Finally, a global vibration state virtual sensing system of rotating bladed disk is constructed, and the key technologies are theoretically analyzed and verified, and the global state sensing of the dynamic response field is realized. This method can obtain more comprehensive vibration information of bladed disk on the basis of existing testing methods, which provides a new theoretical framework for on-line monitoring of rotating bladed disks, and provides effective data support for fatigue analysis and reliability prediction of bladed disks.

Key words: rotating bladed disk, digital twin, virtual sensing, dynamic response field, three-dimensional visualization

CLC Number:

TH17
TP391

LI Hongkun, WEI Daitong, CHEN Yugang, XU Shuben. A Full-field Sensing Method for Vibration State of Rotating Bladed Disks Driven by Digital Twin[J]. Journal of Mechanical Engineering, 2023, 59(21): 270-282.

References

[1] DIAMOND D H, HEYNS P S, OBERHOLSTER A J. Improved blade tip timing measurements during transient conditions using a state space model[J]. Mechanical Systems and Signal Processing, 2019, 122:555-579.
[2] KARMALITA V. Yule series model application for blade tip timing readouts processing resulting in blade oscillation characteristics estimation[J]. Journal of Nondestructive Evaluation, Diagnostics and Prognostics of Engineering Systems, 2018, 1(4):041002.
[3] BATTIATO G, FIRRONE C M, BERRUTI T M. Forced response of rotating bladed disks:Blade Tip-Timing measurements[J]. Mechanical Systems and Signal Processing, 2017, 85:912-926.
[4] LIU Meiru, TENG Guangrong, XIAO Xiao, et al. Vibration measurement of turbine rotor blades of aero-engine based on blade tip-timing[J]. Journal of Aerospace Power, 2020, 35(9):1954-1963.
[5] DIAMOND D H, STEPHAN H P. A novel method for the design of proximity sensor configuration for rotor blade tip timing[J]. Journal of Vibration and Acoustics, 2018, 140(6):061003.
[6] ZHANG Jilong, DUAN Fajie, NIU Guangyue, et al. A blade tip timing method based on a microwave sensor[J]. Sensors, 2017, 17(5):1097.
[7] TAO Fei, CHENG Jiangfeng, QI Qinglin, et al. Digital twin-driven product design, manufacturing and service with big data[J]. The International Journal of Advanced Manufacturing Technology, 2018, 94(9):3563-3576.
[8] RAJRATNAKHARAT, BAVANE V, JADHAO S, et al. Digital twin:manufacturing excellence through virtual factory replication[C]//Proceedings of the NC-RACE 18(Recent Advances in Science and Engineering). Shegaon, 2018, 96-125.
[9] RASHEED A, SAN O, KVAMSDAL T. Digital Twin:values, challenges and enablers from a modeling perspective[J]. IEEE Access, 2020, 8(1):21980-22012.
[10] WRIGHT L, DAVIDSON S. How to tell the difference between a model and a digital twin[J]. Advanced Modeling and Simulation in Engineering Sciences, 2020, 7(1):1-13.
[11] TAO Fei, ZHANG Meng, LIU Yushan, et al. Digital twin driven prognostics and health management for complex equipment[J]. CIRP Annals, 2018, 67(1):169-72.
[12] WANG Jinjiang, YE Lunkuan, GAO Robert X, et al. Digital twin for rotating machinery fault diagnosis in smart manufacturing[J]. International Journal of Production Research, 2018, 57:3920-3934.
[13] BOTZ M, EMIROGLU A, OSTERMINSKI K, et al. Monitoring and modeling of a wind turbine support structure to create a digital twin[J]. Beton-und Stahlbetonbau, 2020, 115(5):342-354.
[14] JOHANSEN S S, NEJAD A R. On digital twin condition monitoring approach for drive trains in marine applications[C]//Proceedings of the ASME-the International Conference on Ocean, Offshore and Arctic Engineering. United kingdom, 2019, 1-10.
[15] ZHOU Yu, XING Tong, SONG Yue, et al. Digital twin driven geometric optimization of centrifugal impeller with free-form blades for five-axis flank milling[J]. Journal of Manufacturing Systems, 2020, 58:22-35.
[16] ZHANG Xuqian, ZHU Wenhua. Application framework of digital twin-driven product smart manufacturing system:A case study of aeroengine blade manufacturing[J]. International Journal of Advanced Robotic Systems, 2019, 16(5):1-16.
[17] HU Dongfang, WANG Weimin, ZHANG Xulong, et al. On-line real-time mistuning identification and model calibration method for rotating blisks based on blade tip timing(BTT)[J]. Mechanical Systems and Signal Processing, 2021, 147:107074.
[18] GUIVARCH D, MERMOZ E, MARINO Y, et al. Creation of helicopter dynamic systems digital twin using multibody simulations[J]. CIRP Annals, 2019, 68(1):133-136.
[19] 陶飞,刘蔚然,刘检华,等. 数字孪生及其应用探索[J]. 计算机集成制造系统, 2018, 24(1):1-18. TAO Fei, LIU Weiran, LIU Jianhua, et al. Digital twin and its potential application exploration[J]. Computer Integrated Manufacturing System, 2018, 24(1):1-18.
[20] 张霖. 关于数字孪生的冷思考及其背后的建模和仿真技术[J]. 系统仿真学报, 2020, 32(4):1-10. ZHANG Lin. Cold thinking about digital twins and the modeling and simulation techniques behind them[J]. Journal of System Simulation, 2020, 32(4):1-10.
[21] 陶飞,刘蔚然,张萌,等. 数字孪生五维模型及十大领域应用[J]. 计算机集成制造系统, 2019, 25(1):1-18. TAO Fei, LIU Weiran, ZHANG Meng, et al. Five-dimension digital twin model and its ten application[J]. Computer Integrated Manufacturing System, 2019, 25(1):1-18.
[22] WEI Daitong, LI Hongkun, CHEN Yugang, et al. A novel model reduction technique for mistuned blisks based on proper orthogonal decomposition in frequency domain[J]. Aerospace Science and Technology, 2022, 121:107320.
[23] LEON R L, TRAINOR K. Monitoring systems for steam turbine blade faults[J]. Pollutants, 1990, 24:12-15.
[24] AL-BEDOOR B O. Blade vibration measurement in turbo-machinery:Current status[J]. The Shock and Vibration Digest, 2002, 34(6):455-461.
[25] 张玉贵. 烟气轮机叶片振动的非接触式在线监测关键技术研究[D]. 天津:天津大学, 2008. ZHANG Yugui. Key technology research on non-contact online monitoring for fume turbine blade vibration[D]. Tianjin:Tianjin University, 2008.
[26] 王宇华,段发阶,叶声华,等. 涡轮机叶片振动的非接触测量[J]. 宇航计测技术, 2002, 22(2):20-24. WANG Yuhua, DUAN Fajie, YE Shenghua, et al. Noncontact vibration measurement on turbines rotor blades[J]. Journal of Astronautic Metrology and Measurement, 2002, 22(2):20-24.
[27] 韩中合,张万杰,刘江. 基于单叶顶传感器非接触在线测量叶片振动间断相位法的研究[J]. 华北电力大学学报, 2007, 34(4):56-59. HAN Zhonghe, ZHANG Wanjie, LIU Jiang. Study on discontinuous phase method of noncontact on-line monitoring turbine blade vibration based on single tip sensor[J]. Journal of North China Electric Power University, 2007, 34(4):56-59.
[28] WAGNER M, SCHULZE A, VOSSIEK M, et al. Novel microwave vibration monitoring system for industrial power generating turbines[C]//Proceedings of the ARFTG Conference Digest-Spring. IEEE Xplore, 1998, 33:143-146.
[29] 杨海燕,刘启洲. 叶片裂纹故障的多普勒在线监测技术仿真研究[J]. 航空动力学报, 1999, 14(1):70-74. YANG Haiyan, LIU Qizhou. Simulation study on doppler on-line monitoring technology for blade crack fault[J]. Journal of Aerospace Power, 1999, 14(1):70-74.
[30] AL-BEDOOR B O. Dynamic model of coupled shaft torsional and blade bending deformations in rotors[J]. Computer Methods in Applied Mechanics and Engineering, 1999, 169(1):177-90.
[31] AL-BEDOOR B O. Reduced-order nonlinear dynamic model of coupled shaft-torsional and blade-bending vibrations in rotors[J]. Journal of Engineering for Gas Turbines & Power, 2001, 123(1):82-87.
[32] SHEGELSKIMARK R A, STOKERJAMIE S, KELLETTIAN. Tipping time of a holonomic quantum cylinder[J]. Canadian Journal of Physics, 2011, 89(9):903-913.
[33] HEATH S. A new technique for identifying synchronous resonances using tip-timing[J]. Journal of Engineering for Gas Turbines and Power, 2000, 122(2):219-225.
[34] 欧阳涛,段发阶,李孟麟. 恒速下旋转叶片同步振动辨识方法[J]. 天津大学学报, 2011, 44(8):742-746. OUYANG Tao, DUAN Fajie, LI Menglin. Method for identifying rotating blade synchronous vibration at constant speed[J]. Journal of Tianjin University, 2011, 44(8):742-746.