Pose prediction based on dynamic modeling and virtual prototype simulation of shield tunnelling machine

Abstract

Compared with traditional feedback control, predictive control can eliminate the lag of pose control and avoid the snakelike motion of shield machines. Therefore, a shield pose prediction model was proposed based on dynamic modeling. Firstly, the dynamic equations of shield thrust system were established to clarify the relationship between force and movement of shield machine. Secondly, an analytical model was proposed to predict future multistep pose of the shield machine. Finally, a virtual prototype model was developed to simulate the dynamic behavior of the shield machine and validate the accuracy of the proposed pose prediction method. Results reveal that the model proposed can predict the shield pose with high accuracy, which can provide a decision basis whether for manual or automatic control of shield pose.

References

[1] Li X-F, Gong G-F. Predictive control of slurry pressure balance in shield tunneling using diagonal recurrent neural network and evolved particle swarm optimization [J]. Automation in Construction, 2019, 107(11): 102928

[2] Yang H-Y, Hu S, Gong G-F, et al.. Electrohydraulic proportional control of thrust system for shield tunneling machine [J]. Automation in Construction, 2009, 18: 950-956

[3] Tang X-Q, Deng K-S, Wang L-P, et al.. Research on natural frequency characteristics of thrust system for EPB machines [J]. Automation in Construction, 2012, 22: 491-497

[4] Min F-L, Du J-R, Zhang N, et al.. Experimental study on property change of slurry and filter cake of slurry shield under seawater intrusion [J]. Tunnelling and Underground Space Technology, 2019, 88: 290-299

[5] Zhang W-J, Koizumi A. Behavior of composite segment for shield tunnel [J]. Tunnelling and Underground Space Technology, 2010, 25(4): 325-332

[6] Yan T, Shen S-L, Zhou A-N. Identification of geological characteristics from construction parameters during shield tunnelling [J]. Acta Geotechnica, 2023, 18(1): 535-551

[7] Zhang N, Shen S-L, Zhou A-N. A new index for cutter life evaluation and ensemble model for prediction of cutter wear [J]. Tunnelling and Underground Space Technology Incorporating Trenchless Technology Research, 2023, 131: 104830

[8] Shen S-L, Yan T, Zhou A-N. Estimating locations of soil - rock interfaces based on vibration data during shield tunnelling [J]. Automation in Construction, 2023, 150: 104813

[9] Yan T, Shen S-L, Zhou A-N. GFII: A new index to identify geological features during shield tunnelling [J]. Tunnelling and Underground Space Technology Incorporating Trenchless Technology Research, 2023, 142: 105440

[10] Shen S-L, Zhang N, Zhou A-N. Investigation of disc cutter wear during shield tunnelling in weathered granite: A case study [J]. Tunnelling and Underground Space Technology Incorporating Trenchless Technology Research, 2023, 140: 105323

[11] Gong C-J, Xie C-R, Lin Z-Q, et al.. Ground deformation prediction induced by shield tunnelling considering existing multi-story buildings [J]. Journal of Central South University, 2023, 30(4): 1373-1387

[12] Fang Q, Du J-M, Li J-Y, et al.. Settlement characteristics of large-diameter shield excavation below existing subway in close vicinity [J]. Journal of Central South University, 2021, 28(3): 882-897

[13] Liu X-Y, Fang H-Y, Wang F-M, et al.. Horizontal trap-door investigation on face failure zone of shield tunneling in sands [J]. Journal of Central South University, 2021, 28(3): 866-881

[14] Huang H-W, Chang J-Q, Zhang D-M, et al.. Machine learning-based automatic control of tunneling posture of shield machine [J]. Journal of Rock Mechanics and Geotechnical Engineering, 2022, 14(4): 1153-1164

[15] Wang L-T, Yang X, Gong G-F, et al.. Pose and trajectory control of shield tunneling machine in complicated stratum [J]. Automation in Construction, 2018, 93: 192-199

[16] Ye G-L, Han L, Yadav S K, et al.. Investigation on the tail brush induced loads upon segmental lining of a shield tunnel with small overburden [J]. Tunnelling and Underground Space Technology, 2020, 97: 103283

[17] Festa D, Broere W, Bosch J W. Kinematic behaviour of a Tunnel Boring Machine in soft soil: Theory and observations [J]. Tunnelling and Underground Space Technology, 2015, 49: 208-217

[18] Zhou C, Xu H-C, Ding L-Y, et al.. Dynamic prediction for attitude and position in shield tunneling: A deep learning method [J]. Automation in Construction, 2019, 105(SEP.): 102840

[19] Shen S-L, Elbaz K, Shaban W M, et al.. Realtime prediction of shield moving trajectory during tunnelling [J]. Acta Geotechnica, 2022, 17(4): 1533-1549

[20] Hu M, Wu B-J, Bai X. A real-time shield attitude deviation prediction method based on data drive [C]. 2019 IEEE 4th Advanced Information Technology, Electronic and Automation Control Conference (IAEAC), 2019, Chengdu, China, IEEE 2749-2753

[21] Zhang N, Zhang N, Zheng Q, et al.. Real-time prediction of shield moving trajectory during tunnelling using GRU deep neural network [J]. Acta Geotechnica, 2022, 17(4): 1167-1182

[22] Li L, Hu C-M, Hou Y-J. Prediction analysis of shield vertical attitude based on GRU [J]. Journal of Physics: Conference Series, 2020, 1651(1): 012032

[23] Xiao H-H, Xing B, Wang Y-J, et al.. Prediction of shield machine attitude based on various artificial intelligence technologies [J]. Applied Sciences, 2021, 11(21): 10264

[24] Wang P, Kong X-G, Guo Z-K, et al.. Prediction of axis attitude deviation and deviation correction method based on data driven during shield tunneling [J]. IEEE Access, 2019, 7: 163487-163501

[25] Li X-H, Yu H-B, Yuan M-Z, et al.. Dynamic modeling and analysis of shield TBM cutterhead driving system [J]. Journal of Dynamic Systems, Measurement, and Control, 2010, 132(4): 1

[26] Li X-H, Yu H-B, Yuan M-Z, et al.. Research on dynamic models and performances of shield tunnel boring machine cutterhead driving system [J]. Advances in Mechanical Engineering, 2013, 5: 359757

[27] Zhang D, Su X-P, Gao Z, et al.. Design, analysis and fabrication of a novel three degrees of freedom parallel robotic manipulator with decoupled motions [J]. International Journal of Mechanics and Materials in Design, 2013, 9(3): 199-212

[28] Wang X-Y, Yuan D-J, Wang X-Y, et al.. Kinematic analysis and virtual prototype simulation of the thrust mechanism for shield machine [J]. Applied Sciences, 2022, 12(3): 1431

RIGHTS & PERMISSIONS

Central South University