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2025 Vol.35, Issue 1 Preview Page

Original Article

Prediction of Pick Acting Forces Using an Random Forest Model based on Mechanical Properties of Rocks and Cutting Parameters

랜덤포레스트 모델을 이용한 암석의 역학적 물성과 절삭조건 기반의 픽 커터 작용력 예측

Mohammad Sharghi1
,
Hoyoung Jeong2*
Sharghi Mohammad1
,
정 호영2*
1Postdoctoral Researcher, Department of Energy Resources Engineering, Pukyong National University
2Assistant Professor, Department of Energy Resources Engineering, Pukyong National University
1국립부경대학교 에너지자원공학과 박사후연구원
2국립부경대학교 에너지자원공학과 조교수
*Corresponding Author
28 February 2025. pp. 55-70
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Abstract

Rock cutting is a critical process in mining and civil engineering applications, with acting forces of cutting tools playing a pivotal role in determining excavation efficiency, tool wear, and energy consumption. This study presents a comprehensive analysis of predicting mean normal force and mean cutting force using an advanced machine learning approach. The research leverages a robust dataset of 195 experimental samples encompassing diverse rock types, cutting tool geometries, and operational parameters. A two-stage modeling methodology was employed, initially establishing baseline correlations through multivariate linear regression, followed by an optimized Random Forest model with systematic hyperparameter tuning via randomized search cross-validation. The linear regression analysis revealed moderate predictive capabilities, with R2 values of 0.743 for FNm and 0.674 for FCm. In contrast, the optimized RF model demonstrated exceptional performance, achieving R2 values of 0.993 (training) and 0.983 (testing) for FNm, and 0.972 (training) and 0.908 (testing) for FCm. Feature importance analysis highlighted the dominance of uniaxial compressive strength in predicting normal force, while cutting force prediction demonstrated a more complex interaction of multiple parameters.

Keywords
Pick cutter
Acting forces
Cutting parameters
Mechanical properties of rock
Random forest

기계화 암석 절삭은 토목 및 자원개발 분야에서 중요하게 활용되고 있으며, 절삭도구의 작용력은 굴착 효율, 커터마모, 에너지 효율을 결정하는 데 핵심적인 역할을 한다. 본 연구에서는 머신러닝기법을 적용하여 픽 커터의 평균 수직력과 평균 절삭력을 예측하기 위한 연구를 수행하였다. 머신러닝모델의 훈련을 위해 다양한 암종, 커터의 형상 변수, 절삭조건을 포함하는 195개의 선형절삭시험 데이터세트를 구축하여 활용하였다. 모델링은 두 단계로 진행되었으며, 먼저 다변수 선형 회귀 분석을 통해 기초 상관관계를 설정한 후, 무작위 탐색 교차 검증을 통한 체계적인 하이퍼파라미터 튜닝을 거쳐 최적화된 랜덤 포레스트(RF) 모델을 구축하였다. 선형 회귀 분석 결과, 평균 수직력에 대한 결정계수(R2) 값은 0.743, 평균 절삭력은 0.674로 중간 수준의 예측 성능을 보였다. 반면, 최적화된 랜덤포레스트 모델은 우수한 성능을 나타내었다, 평균수직력 예측에서는 훈련 데이터에서 R2 = 0.993, 테스트 데이터에서 R2 = 0.983을 기록하였고, 평균절삭력 예측에서는 훈련 데이터에서 R2 = 0.972, 테스트 데이터에서 R2 = 0.908을 달성하였다. 각 작용력에 미치는 입력변수의 중요도를 분석한 결과, 수직력 예측에서는 일축 압축 강도가 가장 중요한 영향을 미쳤으며, 절삭력 예측에서는 여러 매개변수가 복합적으로 작용하는 것으로 나타났다.

키워드
픽 커터
작용력
절삭조건
암석의 역학적 물성
랜덤포레스트
References
1

Altindag, R., 2003, Correlation of specific energy with rock brittleness concepts on rock cutting, Journal of The South African Institute of Mining and Metallurgy, 103(3), 163-171.

2

Avunduk, E., Tumac, D., and Atalay, A.K., 2014, Prediction of roadheader performance by artificial neural network, Tunnelling and Underground Space Technology, 44, 3-9.

10.1016/j.tust.2014.07.003
3

Balci, C., Demircin, M.A., Copur, H., and Tuncdemir, H., 2004, Estimation of optimum specific energy based on rock properties for assessment, The Journal of The South African Institute of Mining and Metallurgy, 104(11), 633-642.

4

Bilgin, N., Copur, H., Balci, C., and Tumac, D., 2008, The selection of a TBM using full scale laboratory tests and comparison of measured and predicted performance values in Istanbul Kozyatagi-Kadikoy metro tunnels, in: World Tunnel Congress 2008 - Underground Facilities for Better Environment and Safety, India, pp. 1509-1517.

5

Bilgin, N., Demircin, M.A., Copur, H., Balci, C., Tuncdemir, H., and Akcin, N., 2006, Dominant rock properties affecting the performance of conical picks and the comparison of some experimental and theoretical results, Int. J. Rock Mech. Min. Sci., 43, 139-156.

10.1016/j.ijrmms.2005.04.009
6

Chang, S.H., Choi, S.W., Bae, G.J., and Jeon, S., 2006, Performance prediction of TBM disc cutting on granitic rock by the linear cutting test, Tunn. Undergr. Sp. Tech., 21, 271.

10.1016/j.tust.2005.12.131
7

Copur, H., 1999, Theoretical and experimental studies of rock cutting with drag bits toward the development of a performance prediction model for roadheaders, PhD Thesis, Colorado School of Mines, USA.

8

Evans, I., 1961, A theory of the basic mechanics of coal ploughing, in: G.B. Clark (Ed.), Proceedings of the International Symposium on Mining Research, Oxford: Pergamon Press, University of Missouri, pp. 761-768. https://api.semanticscholar.org/Corpus ID:114631164.

10.1016/B978-1-4832-8307-4.50053-2
9

Evans, I., 1984, A theory of the picks cutting force for point-attack, International Journal of Mining Engineering, 2, 63-71.

10.1007/BF00880858
10

Fathipour-Azar, H., 2023, Mean cutting force prediction of conical picks using ensemble learning paradigm, Rock Mech. Rock Eng., 56, 221-236.

10.1007/s00603-022-03095-0
11

Gao, K., Du, C., Jiang, H., and Liu, S., 2013, A theoretical model for predicting the Peak Cutting Force of conical picks, Fracture and Structural Integrity, 8(27), 43-52.

10.3221/IGF-ESIS.27.06
12

Gehring, K., 2009, The influence of TBM design and machine features on performance and tool wear in rock, Geomechanics and Tunnelling, 2, 140-155.

10.1002/geot.200900015
13

Geng, Q., Huang, Y., Chen, J., Wang, X., Liu, W., Luo, Y., Zhang, Z., and Ye, M., 2012, Prediction of rock-breaking forces of tunnel boring machine (TBM) disc cutter based on machine learning methods, Procedia Economics and Finance. https://ssrn.com/abstract=4997783.

14

Geng, Q., Wei, Z., and Hao, M., 2016, An experimental research on the rock cutting process of the gage cutters for rock tunnel boring machine (TBM), Tunn. Undergr. Sp. Tech., 52, 182-191.

10.1016/j.tust.2015.12.008
15

Gertsch, R., Gertsch, L., and Rostami, J., 2007, Disc cutting tests in Colorado Red Granite: Implications for TBM performance prediction, Int. J. Rock Mech. Min. Sci., 44, 238-246.

10.1016/j.ijrmms.2006.07.007
16

Goktan, R.M., 1990, Effect of cutter pick rake angle on the failure pattern of high-strength rocks, Mining Science and Technology, 11, 281-285.

10.1016/0167-9031(90)90981-W
17

Goktan, R.M., and Yilmaz, N. G., 2005, A new methodology for the analyses of the relationship between rock brittleness index and drag pick cutting efficiency, Journal of The South African Institute of Mining and Metallurgy, 105(10), 727-734.

18

Grafe, B., 2022, Cutting force component-based rock differentiation utilizing machine learning, Technical University Bergakademie Freiberg.

19

Hu, M., Li, B., Zhang, B., Wang, R., and Chen, L., 2021, Improved SVR method for predicting the cutting force of a TBM cutter using linear cutting machine test data, KSCE Journal of Civil Engineering, 25, 4425-4442.

10.1007/s12205-021-2339-0
20

Huang, H., Lecampion, B., and Detournay, E., 2013, Discrete element modeling of tool-rock interaction I: rock cutting, Int. J. Numer. Anal. Methods Geomech., 37, 1913-1929.

10.1002/nag.2113
21

Jeong, H., and Jeon, S., 2018, Characteristic of size distribution of rock chip produced by rock cutting with a pick cutter, Geomechanics and Engineering 15(3), 811-822.

22

Jeong, H., Cho, J.W., Jeon, S., and Rostami, J., 2016, Performance assessment of hard rock TBM and rock boreability using punch penetration test, Rock Mech. Rock Eng., 49, 1517-1532.

10.1007/s00603-015-0834-7
23

Jeong, H., Choi, S., and Jeon, S., 2020a, Effect of skew angle on the cutting performance and cutting stability of point-attack type picks, Tunn. Undergr. Sp. Tech., 103, 103507.

10.1016/j.tust.2020.103507
24

Jeong, H., Choi, S., Lee, S., and Jeon, S., 2020b, Rock cutting simulation of point attack picks using the smooth particle hydrodynamics technique and the cumulative damage model, Applied Sciences, 10(15), 5314.

10.3390/app10155314
25

Jeong, H., Choi, S., and Lee, Y.K., 2023, Evaluation of Cutting Performance of a TBM Disc Cutter and Cerchar Abrasivity Index Based on the Brittleness and Properties of Rock, Applied Sciences, 13(4), 2612.

10.3390/app13042612
26

Li, X., Wang, S., Ge, S., Malekian, R., and Li, Z., 2018, A theoretical model for estimating the peak cutting force of conical picks, Exp. Mech., 58, 709-720.

10.1007/s11340-017-0372-1
27

Li, X., Zhang, Y., and Sun, X., 2021, Numerical analysis for rock cutting force prediction in the tunnel boring process, Int. J. Rock Mech. Min. Sci., 144, 104696.

10.1016/j.ijrmms.2021.104696
28

Liu, Z., Liu, Y., Sun, J., Yang, J., Yang, B., and Li, D., 2024, Intelligent evaluation of mean cutting force of conical pick by boosting trees and Bayesian optimization, J. Cent. South. Univ., 31, 3948-3964.

10.1007/s11771-024-5659-7
29

Lu, Z., Zeng, Q., Wang, Z., Li, X., and Gao, K., 2019, Experimental and numerical studies on rock cutting with saw blade and conical pick combined cutting method, Math. Probl. Eng.

10.1155/2019/5046873
30

Moon, T., and Oh, J., 2012, A study of optimal rock-cutting conditions for hard rock TBM using the discrete element method, Rock Mech. Rock Eng., 45, 837-849.

10.1007/s00603-011-0180-3
31

Morshedlou, A., Rostami, J., and Moradian, O., 2024, Estimation of cutting forces acting on conical cutters based on rock properties and the contact area between cutter tip and rock, Rock Mech. Rock Eng., 57, 10307-10328.

10.1007/s00603-024-04068-1
32

Nishimatsu, Y., 1972, The mechanics of rock cutting, International Journal of Rock Mechanics and Mining Sciences & Geomechanics Abstracts, 9(2), 261-270.

10.1016/0148-9062(72)90027-7
33

Pan, Y., Liu, Q., Liu, J., Peng, X., and Kong, X., 2018, Full-scale linear cutting tests in Chongqing sandstone to study the influence of confining stress on rock cutting forces by TBM disc cutter, Rock Mech. Rock Eng., 51, 1697-1713.

10.1007/s00603-018-1412-6
34

Pan, Y., Liu, Q., Peng, X., Liu, Q., Liu, J., Huang, X., Cui, X., and Cai, T., 2019, Full-scale linear cutting tests to propose some empirical formulas for TBM disc cutter performance prediction, Rock Mech. Rock Eng., 52, 4763-4783.

10.1007/s00603-019-01865-x
35

Rojek, J., Onate, E., Labra, C., and Kargl, H., 2011, Discrete element simulation of rock cutting, Int. J. Rock Mech. Min. Sci., 48, 996-1010.

10.1016/j.ijrmms.2011.06.003
36

Roxborough, F.F., and Phillips, H.R., 1975, Rock excavation by disc cutter, Int. J. Rock Mech. Min. Sci. Geomech. Abstr., 12(12), 361-366.

10.1016/0148-9062(75)90547-1
37

Saksala, T., 2023, 3D continuum modelling of PDC cutting of rock with a simple contact-erosion scheme, Applied Sciences, 13.

10.3390/app13053219
38

Snowdon, R.A., Ryley, M.D., and Temporal, J., 1982, A study of disc cutting in selected British rocks, Int. J. Rock Mech. Min. Sci. Geomech. Abstr., 19(3), 107-121.

10.1016/0148-9062(82)91151-2
39

Tiryaki, B., Boland, J.N., and Li, X.S., 2010, Empirical models to predict mean cutting forces on point-attack pick cutters, Int. J. Rock Mech. Min. Sci., 47, 858-864.

10.1016/j.ijrmms.2010.04.012
40

Tiryaki, B., and Dikmen, A.C., 2006, Effects of rock properties on specific cutting energy in linear cutting of sandstones by picks, Rock Mech. Rock Eng., 39, 89-120.

10.1007/s00603-005-0062-7
41

Wang, X., Wang, Q.F., Liang, Y.P. Su, O., and Yang, L., 2018, Dominant cutting parameters affecting the specific energy of selected sandstones when using conical picks and the development of empirical prediction models, Rock Mech. Rock Eng., 51, 3111-3128.

10.1007/s00603-018-1522-1
42

Wicaksana, Y., Jeong, H., and Jeon, S., 2021, Numerical simulation of rock cutting process induced by a pick cutter considering dynamic properties of rock at intermediate strain rate, Bulletin of Engineering Geology and the Environment, 80, 9049-9069.

10.1007/s10064-021-02471-4
43

Xue, Y., Shu, L., Zhao, L., Luo, W., and Guo, Y., 2025, MatDEM-based study of disc cutter force model in open TBM tunnels: Incorporating installation radius and synergistic effects, Underground Space, 20, 293-310.

10.1016/j.undsp.2024.02.008
44

Yang, Z., Hu, Y., Xu, M., Pang, H., Gu, Y., and Zheng, B., 2024, Research on the rock cutting performance and feasibility verification of small-scale rotary cutting test for disc cutter, Sci. Rep., 14.

10.1038/s41598-024-80059-039558032PMC11573981
45

Yilmaz, N.G., Yurdakul, M., and Goktan, R.M., 2007, Prediction of radial bit cutting force in high-strength rocks using multiple linear regression analysis, Int. J. Rock Mech. Min. Sci., 44, 962-970.

10.1016/j.ijrmms.2007.02.005
46

Zeng, Q., Wang, Z., Lu, Z., Wan, L., Liu, Z., and Zhang, X., 2021, Research on cutting performance and fatigue life of conical pick in cutting rock process, Sci. Prog., 104.

10.1177/0036850421105029334842471PMC10359651
47

Zhang, G., Dang, W., Herbst, M., and Song, Z., 2020, Complex analysis of rock cutting with consideration of rock-tool interaction using distinct element method (DEM), Geomechanics and Engineering, 20, 421-432.

48

Zheng, S., Gong, Q., Jiang, Y., Cao, Y., Liu, Y., and Han, B., 2025, Laboratory experimental study of a real-time monitoring system for TBM cutter force, KSCE Journal of Civil Engineering, 29, 100003.

10.1016/j.kscej.2024.100003
49

Zhou, J., Dai, Y., Tao, M., Khandelwal, M., Zhao, M., and Li, Q., 2023, Estimating the mean cutting force of conical picks using random forest with salp swarm algorithm, Results in Engineering, 17, 100892.

10.1016/j.rineng.2023.100892
Information
  • Publisher :Korean Society for Rock Mechanics and Rock Engineering
  • Publisher(Ko) :한국암반공학회
  • Journal Title :Tunnel and Underground Space
  • Journal Title(Ko) :터널과 지하공간
  • Volume : 35
  • No :1
  • Pages :55-70
  • Received Date : 2025-02-07
  • Revised Date : 2025-02-24
  • Accepted Date : 2025-02-24
  • DOI :https://doi.org/10.7474/TUS.2025.35.1.055
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