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Analysis of disc cutter replacement based on wear patterns using artificial intelligence classification models

  • Yunhee Kim (Department of Civil and Environmental Engineering, Dongguk University) ;
  • Jaewoo Shin (Department of Civil and Environmental Engineering, Dongguk University) ;
  • Bumjoo Kim (Department of Civil and Environmental Engineering, Dongguk University)
  • Received : 2023.11.28
  • Accepted : 2024.02.07
  • Published : 2024.09.25

Abstract

Disc cutters, used as excavation tools for rocks in a Tunnel Boring Machine (TBM), naturally undergo wear during the tunneling process, involving crushing and cutting through the ground, leading to various wear types. When disc cutters reach their wear limits, they must be replaced at the appropriate time to ensure efficient excavation. General disc cutter life prediction models are typically used during the design phase to predict the total required quantity and replacement locations for construction. However, disc cutters are replaced more frequently during tunneling than initially planned. Unpredictable disc cutter replacements can easily diminish tunneling efficiency, and abnormal wear is a common cause during tunneling in complex ground conditions. This study aims to overcome the limitations of existing disc cutter life prediction models by utilizing machine data generated during tunneling to predict disc cutter wear patterns and determine the need for replacements in real-time. Artificial intelligence classification algorithms, including K-nearest Neighbors (KNN), Support Vector Machine (SVM), Decision Tree (DT), and Stacking, are employed to assess the need for disc cutter replacement. Binary classification models are developed to predict which disc cutters require replacement, while multi-class classification models are fine-tuned to identify three categories: no replacement required, replacement due to normal wear, and replacement due to abnormal wear during tunneling. The performance of these models is thoroughly assessed, demonstrating that the proposed approach effectively manages disc cutter wear and replacements in shield TBM tunnel projects.

Keywords

Acknowledgement

This research was supported by the Basic Science Research Program through the National Research Foundation of Korea (NRF) funded by the Ministry of Education (NRF-2022R1F1A1065540).

References

  1. Afradi, A., Ebrahimabadi, A. and Hallajian, T. (2021), "Prediction of the number of consumed disc cutters of tunnel boring machine using intelligent methods", Mining of Mineral Deposits.
  2. Bruland, A. (1988), "Hard rock tunnel boring", Dissertation, Norwegian University of Science and Technology.
  3. Butt, S. and Meschke, G. (2021). "Interaction of cutting disc with heterogeneous ground", PAMM, 20(1). https://doi.org/10.1002/pamm.202000060.
  4. Connors, R. (2017), "The challenges of tunnelling with slurry shield machines in mixed ground", The David Sugden Young Engineers Writing Award.
  5. Ellecosta, P., Kasling, H. and Thuro, K. (2018), "Tool wear in TBM hard rock drilling-backgrounds and special phenomena", Geomech. Tunn., 11(2), 142-148. https://doi.org/10.1002/geot.201800006.
  6. Fang, Y., Yao, Z., Xu, W., Tian, Q., He, C. and Liu, S. (2021), "The performance of TBM disc cutter in soft strata: A numerical simulation using the three-dimensional RBD-DEM coupled method", Eng. Fail. Anal., 119, 104996. https://doi.org/10.1016/j.engfailanal.2020.104996.
  7. Farrokh, E. (2013), "Study of utilization factor and advance rate of hard rock TBMs", PhD Thesis. PSU.
  8. Frenzel, C., Kasling, H. and Thuro, K. (2008), "Factors influencing disc cutter wear", Geomech. Tunn., 1(1), 55-60. https://doi.org/10.1002/geot.200800006.
  9. Gehring, K. (1995), "Leistungs- und Verschleissprognose im maschinellen Tunnelbau", Felsbau., 13(6), 439-448.
  10. Jeong, H., Zhang, N. and Jeon, S. (2018), "Review of technical issues for shield TBM tunneling in difficult grounds", J. Korean Tunn. Undergr. Sp. Assoc., 28(1), 1-24.
  11. Karami, M., Zare, S. and Rostami, J. (2021). "Tracking of disc cutter wear in TBM tunneling: a case study of Kerman water conveyance tunnel", Bull. Eng. Geol. Environ., 80, 201-219. https://doi.org/10.1007/s10064-020-01931-7.
  12. Kovari, K. and Ramoni, M. (2006), "Urban tunnelling in soft ground using TBMs", Proceedings of the International Conference and Exhibition on Tunnelling and Trenchless Technology: Tunnelling and Trenchless technology in the 21st century, Subang Jaya-Selangor Darul Ehsan, January.
  13. Kohavi, R. and Provost, F. (1998). "Glossary of terms", Editorial for the Special Issue On Applications of Machine Learning and the Knowledge Discovery Process.
  14. Kim, D., Khanh, P., Park, S., Oh, J. and Choi, H. (2020), "Determination of effective parameters on surface settlement during shield TBM", Geomech. Eng., 21(2), 153-164. https://doi.org/10.12989/gae.2020.21.2.153.
  15. Kim, K., Oh, J., Lee, H., Kim, D. and Choi, H. (2018), "Critical face pressure and backfill pressure in shield TBM tunneling on soft ground", Geomech. Eng., 15(3), 823-831. https://doi.org/10.12989/gae.2018.15.3.823.
  16. Kim, Y., Hong, J., Shin, J. and Kim, B. (2022), "Shield TBM disc cutter replacement and wear rate prediction using machine learning techniques", Geomech. Eng., 29(3), 249-258. https://doi.org/10.12989/gae.2022.29.3.249.
  17. Lislerud, A. (1997), "Principles of mechanical excavation", Tamrock Corp. POSI VA 97-12.
  18. Macias, F.J. (2016), "Hard rock tunnel boring: Performance predictions and cutter life assessments", Dissertation, Norwegian University of Science and Technology.
  19. Mahmoodzadeh, A., Mohammadi, M., Ibrahim, H.H., Abdulhamid, S.N., Ali, H.F.H., Hasan, A.M. and Mahmud, H. (2021), "Machine learning forecasting models of disc cutters life of tunnel boring machine", Automat. Constr., 128, 103779.
  20. Ministry of Construction & Transportation. (2007), "Development of an optimal excavation design model for rapid tunnel mechanization construction", Construction & Transportation R&D report.
  21. Ren, D.J., Shen, S.L., Arulrajah, A. and Cheng, W.C. (2018), "Prediction model of TBM disc cutter wear during tunnelling in heterogeneous ground", Rock Mech. Rock Eng., 51, 3599-3611. https://doi.org/10.1007/s00603-018-1549-3.
  22. Rezaei, A.H., Shirzehhagh, M. and Golasand, M.R.B. (2019), "EPB tunneling in cohesionless soils: A study on Tabriz Metro settlements", Geomech. Eng., 19(2), 153-165. https://doi.org/10.12989/gae.2019.19.2.153.
  23. Rostami, J. (1997), "Development of a force estimation model for rock fragmentation with disc cutters through theoretical modeling and physical measurement of crushed zone pressure", Dissertation, Colorado School of Mines.
  24. Tharwat, A. (2020), "Classification assessment methods", Appl. Comput. Inform., 17(1), 168-192.
  25. Xiaokang, S., Yusheng, J., Zongyuan, Z., Zhiyong, Y., Zhenyong, W., Jinguo, C. and Quanwei, L. (2023), "TBM disc cutter ring type adaptability and rock-breaking efficiency: Numerical modeling and case study", Geomech. Eng., 34(1), 103-113. https://doi.org/10.12989/gae.2023.34.1.103.
  26. Yang, Z., Sun, Z., Fang, K., Jiang, Y., Gao, H. and Bai, Z. (2021), "Cutting tool wear model for tunnel boring machine tunneling in heterogeneous grounds", Bull. Eng. Geol. Environ., 80(7), 5709-5723. https://doi.org/10.1007/s10064-021-02298-z.
  27. Yu, H., Tao, J., Huang, S., Qin, C., Xiao, D. and Liu, C. (2021), "A field parameters-based method for real-time wear estimation of disc cutter on TBM cutter head", Automat. Constr., 124, 103603. https://doi.org/10.1016/j.autcon.2021.103603.