Intelligent evaluation method for integrity of hydraulic rock mass by coupling multi-source survey information

LI Mingchao; LI Mingze; HAN Shuai; ZHANG Jiawen; ZHAO Wenchao

doi:10.11779/CJGE20220718

Volume 45 Issue 8

Turn off MathJax

Article Contents

Abstract

References

Supplements

Chinese Journal of Geotechnical Engineering > 2023 > 45(8): 1674-1683. > DOI: 10.11779/CJGE20220718

LI Mingchao, LI Mingze, HAN Shuai, ZHANG Jiawen, ZHAO Wenchao. Intelligent evaluation method for integrity of hydraulic rock mass by coupling multi-source survey information[J]. Chinese Journal of Geotechnical Engineering, 2023, 45(8): 1674-1683. DOI: 10.11779/CJGE20220718

Citation:

PDF (2067 KB)

Intelligent evaluation method for integrity of hydraulic rock mass by coupling multi-source survey information

1.
State Key Laboratory of Hydraulic Engineering Simulation and Safety, Tianjin University, Tianjin 300350, China
2.
Architecture and Real Estate Learning, The Hong Kong Polytechnic University, Hongkong 999077, China
3.
Bei Fang Investigation, Design & Research Corporation Limited, Tianjin 300222, China

More Information

Received Date: June 05, 2022
Available Online: February 26, 2023

Graphical Abstract

Abstract

Abstract

The integrity of rock mass is an important parameter in evaluating the quality grade of hydraulic rock mass. The traditional methods often adopt a single index that cannot fully reflect the comprehensive influences of geological conditions such as structural plane, groundwater, and unloading on the evaluation results. An intelligent evaluation method for the integrity of hydraulic rock mass is proposed by coupling with multi-source survey information. Firstly, the synthetic minority oversampling (SMOTE) algorithm is used to balance the survey information data to improve the data set structure. Then the random forest algorithm is used to predict the original rock mass integrity data and the pre-processed data, respectively. Based on the data of actual projects, the validity and applicability are verified, and the predicted results are discussed and analyzed according to different factors affecting the integrity of rock mass. The results show that the proposed method can effectively improve the evaluation accuracy of the integrity of a few rock samples by balancing the data sets. By coupling and mining the deep information of different integrity indexes, the intelligent evaluation of rock mass integrity can be realized, which provides a new method for further assisting the evaluation of rock mass quality.
- rock mass integrity,
- evaluation of rock mass quality,
- multi-source survey information,
- random forest,
- SMOTE

FullText(HTML)

References (30)

References

[1]	刘飞跃, 刘一汉, 杨天鸿, 等. 基于岩芯图像深度学习的矿山岩体质量精细化评价[J]. 岩土工程学报, 2021, 43(5): 968-974. doi: 10.11779/CJGE202105023 LIU Feiyue, LIU Yihan, YANG Tianhong, et al. Meticulous evaluation of rock mass quality in mine engineering based on machine learning of core photos[J]. Chinese Journal of Geotechnical Engineering, 2021, 43(5): 968-974. (in Chinese) doi: 10.11779/CJGE202105023
[2]	梁靖, 崔圣华, 裴向军, 等. 考虑岩体构造损伤的强震大型滑坡启动成因[J]. 岩土工程学报, 2021, 43(6): 1039-1049. doi: 10.11779/CJGE202106007 LIANG Jing, CUI Shenghua, PEI Xiangjun, et al. Initiation mechanism of earthquake-induced large landslides considering structural damage[J]. Chinese Journal of Geotechnical Engineering, 2021, 43(6): 1039-1049. (in Chinese) doi: 10.11779/CJGE202106007
[3]	NIKAFSHAN R H, JALALI Z, JALALIFAR H. Prediction of rock mass rating system based on continuous functions using Chaos–ANFIS model[J]. International Journal of Rock Mechanics and Mining Sciences, 2015, 73: 1-9. doi: 10.1016/j.ijrmms.2014.10.004
[4]	GHOLAMI R, RASOULI V, ALIMORADI A. Improved RMR rock mass classification using artificial intelligence algorithms[J]. Rock Mechanics and Rock Engineering, 2013, 46(5): 1199-1209. doi: 10.1007/s00603-012-0338-7
[5]	ZHANG Y Z, JI H G, LI W G, et al. Research on rapid evaluation of rock mass quality based on ultrasonic borehole imaging technology and fractal method[J]. Advances in Materials Science and Engineering, 2021, 2021: 1-9.
[6]	水利水电工程地质勘察规范: GB 50487—2008[S]. 北京: 中国计划出版社, 2009. Code for Engineering Geological Invcstigation of Water Resources and Hydropower: GB 50487—2008[S]. Beijing: China Planning Press, 2009. (in Chinese)
[7]	BARTON N, LIEN R, LUNDE J. Engineering classification of rock masses for the design of tunnel support[J]. Rock Mechanics, 1974, 6(4): 189-236. doi: 10.1007/BF01239496
[8]	HOEK E, BROWN E T. Practical estimates of rock mass strength[J]. International Journal of Rock Mechanics and Mining Sciences, 1997, 34(8): 1165-1186. doi: 10.1016/S1365-1609(97)80069-X
[9]	许宏发, 陈锋, 王斌, 等. 岩体分级BQ与RMR的关系及其力学参数估计[J]. 岩土工程学报, 2014, 36(1): 195-198. doi: 10.11779/CJGE201401021 XU Hongfa, CHEN Feng, WANG Bin, et al. Relationship between RMR and BQ for rock mass classification and estimation of its mechanical parameters[J]. Chinese Journal of Geotechnical Engineering, 2014, 36(1): 195-198. (in Chinese) doi: 10.11779/CJGE201401021
[10]	李明超, 史博文, 韩帅, 等. 基于对穿声波波速的岩体完整性多尺度评价新指标与分析方法[J]. 岩石力学与工程学报, 2020, 39(10): 2060-2068. https://www.cnki.com.cn/Article/CJFDTOTAL-YSLX202010010.htm LI Mingchao, SHI Bowen, HAN Shuai, et al. New index and analysis method for multi-scale rock mass integrity assessment based on P-wave velocity[J]. Chinese Journal of Rock Mechanics and Engineering, 2020, 39(10): 2060-2068. (in Chinese) https://www.cnki.com.cn/Article/CJFDTOTAL-YSLX202010010.htm
[11]	曹瑞琅, 王玉杰, 赵宇飞, 等. 基于钻进过程指数定量评价岩体完整性原位试验研究[J]. 岩土工程学报, 2021, 43(4): 679-687. doi: 10.11779/CJGE202104010 CAO Ruilang, WANG Yujie, ZHAO Yufei, et al. In-situ tests on quantitative evaluation of rock mass integrity based on drilling process index[J]. Chinese Journal of Geotechnical Engineering, 2021, 43(4): 679-687. (in Chinese) doi: 10.11779/CJGE202104010
[12]	李清波, 杜朋召. 基于边缘阈值分割的钻孔图像RQD自动分析方法研究[J]. 岩土工程学报, 2020, 42(11): 2153-2160. doi: 10.11779/CJGE202011022 LI Qingbo, DU Pengzhao. Automatic RQD analysis method based on information recognition of borehole images[J]. Chinese Journal of Geotechnical Engineering, 2020, 42(11): 2153-2160. (in Chinese) doi: 10.11779/CJGE202011022
[13]	GUO H S, FENG X T, LI S J, et al. Evaluation of the integrity of deep rock masses using results of digital borehole televiewers[J]. Rock Mechanics and Rock Engineering, 2017, 50(6): 1371-1382.
[14]	殷明伦, 张晋勋, 江玉生, 等. 岩体体积节理数表征岩体完整系数的结构面类别修正研究[J]. 岩土力学, 2021, 42(4): 1133-1140. https://www.cnki.com.cn/Article/CJFDTOTAL-YTLX202104027.htm YIN Minglun, ZHANG Jinxun, JIANG Yusheng, et al. Study of correction of the structural plane category based on the rock mass integrity coefficient characterized by the volumetric joint count[J]. Rock and Soil Mechanics, 2021, 42(4): 1133-1140. (in Chinese) https://www.cnki.com.cn/Article/CJFDTOTAL-YTLX202104027.htm
[15]	SONG Y H, XUE H S. Correlations between rock mass intactness index (K_v) and other rock mass classification indices (RMR₈₉ system and GSI)[J]. Bulletin of Engineering Geology and the Environment, 2021, 80(10): 7807-7816.
[16]	PELLS P J, BIENIAWSKI Z T, HENCHER S R, et al. Rock quality designation (RQD): time to rest in peace[J]. Canadian Geotechnical Journal, 2017, 54(6): 825-834.
[17]	DEERE D U. Technical description of rock cores for engineering purpose[J]. Rock Mechanics and Engineering Geology, 1964, 1(1): 17-22.
[18]	张文, 陈剑平, 牛岑岑, 等. 基于三维裂隙网络RQD的确定及最佳测线数量的研究[J]. 岩土工程学报, 2013, 35(2): 321-327. http://www.cgejournal.com/cn/article/id/14979 ZHANG Wen, CHEN Jianping, NIU Cencen, et al. Determination of RQD and number of optimum scanlines based on three-dimensional fracture network[J]. Chinese Journal of Geotechnical Engineering, 2013, 35(2): 321-327. (in Chinese) http://www.cgejournal.com/cn/article/id/14979
[19]	薛秋池, 赵其华, 何云松. 岩体结构面网络模拟的改进与应用[J]. 岩土工程学报, 2016, 38(7): 1351-1356. doi: 10.11779/CJGE201607025 XUE Qiuchi, ZHAO Qihua, HE Yunsong. Improvement and application of network simulation of rock mass discontinuities[J]. Chinese Journal of Geotechnical Engineering, 2016, 38(7): 1351-1356. (in Chinese) doi: 10.11779/CJGE201607025
[20]	ZHANG L Y. Determination and applications of rock quality designation (RQD)[J]. Journal of Rock Mechanics and Geotechnical Engineering, 2016, 8(3): 389-397.
[21]	FALLS S D, YOUNG R P. Acoustic emission and ultrasonic-velocity methods used to characterise the excavation disturbance associated with deep tunnels in hard rock[J]. Tectonophysics, 1998, 289(1/2/3): 1-15.
[22]	段世委, 许仙娥. 岩体完整性系数确定及应用中的几个问题探讨[J]. 工程地质学报, 2013, 21(4): 548-553. https://www.cnki.com.cn/Article/CJFDTOTAL-GCDZ201304012.htm DUAN Shiwei, XU Xiane. Discussion of problems in calculation and application of rock mass integrity coefficient[J]. Journal of Engineering Geology, 2013, 21(4): 548-553. (in Chinese) https://www.cnki.com.cn/Article/CJFDTOTAL-GCDZ201304012.htm
[23]	陈祥, 孙进忠, 谭朝爽, 等. 岩块波速–应力关系及其卸荷效应[J]. 岩土工程学报, 2010, 32(5): 757-761. http://www.cgejournal.com/cn/article/id/13396 CHEN Xiang, SUN Jinzhong, TAN Chaoshuang, et al. Relation between P-wave velocity and stress of rock samples and their unloading effect[J]. Chinese Journal of Geotechnical Engineering, 2010, 32(5): 757-761. (in Chinese) http://www.cgejournal.com/cn/article/id/13396
[24]	水力发电工程地质勘察规范: GB/T 50287—2016[S]. 北京: 中国计划出版社, 2017. Code for Hydropower Engineering Geological Investigation: GB/T 50287—2016[S]. Beijing: China Planning Press, 2017. (in Chinese)
[25]	工程岩体分级标准: GB/T 50218—2014[S]. 北京: 中国计划出版社, 2015. Standard for Engineering Classification of Rock Mass: GB/T 50218—2014[S]. Beijing: China Planning Press, 2015. (in Chinese)
[26]	中小型水利水电工程地质勘察规范: SL 55—1993[S]. 北京: 中国水利电力出版社, 1994. Specification of Engineering Geological Investigation for Medium-Small Water Resources and Hydropower Development: SL 55—1993[S]. Beijing: China Water & Power Press, 1994. (in Chinese)
[27]	韩振华, 张路青, 袁广祥. 基于BQ系统的阿拉善巴彦诺日公NRG01号钻孔岩体质量评价[J]. 工程地质学报, 2019, 27(6): 1208-1215. https://www.cnki.com.cn/Article/CJFDTOTAL-GCDZ201906002.htm HAN Zhenhua, ZHANG Luqing, YUAN Guangxiang. Rock mass quality assessment of borehole NRG01 in bayannuorigong Alxa based on bq-system[J]. Journal of Engineering Geology, 2019, 27(6): 1208-1215. (in Chinese) https://www.cnki.com.cn/Article/CJFDTOTAL-GCDZ201906002.htm
[28]	CHAWLA N V, BOWYER K W, HALL L O, et al. SMOTE: synthetic minority over-sampling technique[J]. Journal of Artificial Intelligence Research, 2002, 16: 321-357.
[29]	BREIMAN L. Random forests[J]. Machine Learning, 2001, 45(1): 5-32.
[30]	陈旭, 俞缙, 李宏, 等. 不同岩性及含水率的岩石声波传播规律试验研究[J]. 岩土力学, 2013, 34(9): 2527-2533. https://www.cnki.com.cn/Article/CJFDTOTAL-YTLX201309015.htm CHEN Xu, YU Jin, LI Hong, et al. Experimental study of propagation characteristics of acoustic wave in rocks with different lithologies and water contents[J]. Rock and Soil Mechanics, 2013, 34(9): 2527-2533. (in Chinese) https://www.cnki.com.cn/Article/CJFDTOTAL-YTLX201309015.htm