Abstract
Fast and accurate prediction for rock strength of intact rock in underground engineerings is the key to ensure the construction safety. Hence, a test method combing ultrasonic wave and rebound for rock strength is established through the test of rock surface hardness and internal defect. Meanwhile, the ultrasonic-rebound-strength model is built by combining traditional mechanical rebound value and new energy rebound value with rock longitudinal wave velocity test value with the methods of bivariate regression analysis, BP neural network and support vector machine (SVM). It applies the models established in the prediction of gneiss strength prediction and determines the optimal model for ultrasonic-rebound strength prediction after analyzing correlation coefficient and relative standard strength deviation. From the prediction results of five test samples, the rock strength prediction model of ultrasonic-rebound method obtained from the SVM method reveals the highest accuracy. At the same time, according to the strength test results of the test samples, the use of new energy resiliometer can greatly improve the prediction accuracy of rock strength.
Similar content being viewed by others
References
Alvarez GM, Babuka R (1999) Fuzzy model for the prediction of unconfined compressive strength of rock samples. Int J Rock Mech Min Sci 36:339–349. https://doi.org/10.1016/s0148-9062(99)00007-8
Crawford B, Alramahi B, Gaillot P, Sanz P, Dedontney N (2012) Mechanical rock properties prediction: deriving rock strength and compressibility from petrophysical properties. Harmon Rock Eng Environ 12:591–596
Deng HF, Li JL, Deng CJ (2011) Analysis of sampling in rock mechanics test and compressive strength prediction methods. Rock Soil Mech 32:3404–3499
Ding HP, Er L, Zhang ZY (2008) Study on correlation of point loading test of rock compressive strength and rebound test. Subgrade Eng. https://doi.org/10.3969/j.issn.1003-8825.2008.05.035
Eze EO (2012) Variability in rock strength prediction using ultrasonic pulse velocity. Adv Mater Res 367:581–587. https://doi.org/10.4028/www.scientific.net/amr.367.581
Eze EO, Osuji SO (2013) Use of Schmidt hardness values in rock strength prediction. Int J Eng Res Africa 11:73–81. https://doi.org/10.4028/www.scientific.net/JERA.11.73
Fang QC, Bejarbaneh BY, Vatandoust M, Armaghani DJ, Murlidhar BR, Mohamad ET (2019) Strength evaluation of granite block samples with different predictive models. Eng Comput. https://doi.org/10.1007/s00366-019-00872-4
Han L, Wang L (2015) The verification of the energy rebound (q value) method and the study of the strength curve. Architect Technol 46:96–97
Li W, Tan ZY (2016a) Comparison on rock strength prediction models based on MLR and LS-SVM. Mining R&D 36:36–40
Li W, Tan ZY (2016b) Prediction of uniaxial compressive strength of rock based on P-wave modulus. Rock Soil Mech 37:381–387. https://doi.org/10.16285/j.rsm.2016.S2.049
Nabaei M, Shahbazi K (2011) A new approach for predrilling the unconfined rock compressive strength prediction. Pet Sci Technol 30:350–359. https://doi.org/10.1080/10916461003752546
National Standard of People’s Republic of China (2013) Standard for test methods of engineering rock mass (GB/T 50266-2013). China Planning Publishing House, Beijing
National Standard of People’s Republic of China (2015) Rebound test hammer (GB/T9138). China Standard Press, Beijing
Standard of China Association for Engineering Construction Standardization (2005) Technical specification for testing strength of concrete by ultrasonic-rebound combined method (CECS 02:2005). China Planning Publishing House, Beijing
Wang RJ (1997) Analysis of acoustic rock classification and rock dynamic mechanical parameters. Geological Publishing House, Beijing
Zhang XG (2000) Introduction to statistical learning theory and support vector machines. Acta Autom Sin 26:36–46
Zhang Z (2014) Application and analysis of core method and rebound method in testing the strength of tunnel lining. Rail Eng. https://doi.org/10.3969/j.issn.1003-1995.2014.05.18
Zhao QH, He ZM (2011) The ubiquitous-joint model and its application in predicting the strength of stratified rock. Instrum Test Model Soil Rock Behav. https://doi.org/10.1061/47633(412)16
Zheng K, Meng QS, Wang R, Wu WJ (2019) Elastic wave properties of coral reef limestone with different structural types. Rock Soil Mech 40:3081–3089. https://doi.org/10.16285/j.rsm.2018.0928
Acknowledgements
This research was financially supported by the Key Research and Development Foundation (2018SF-391) by the Science and Technology Department of Shaanxi Province, the Natural Science Basic Research Project of Shaanxi Province (2017JM5136), the Scientific Research Project of Shaanxi Provincial Department of Education (18JK0402), the President’s Fund Project of Xi’an Technological University (XAGDXJJ16003).
Author information
Authors and Affiliations
Corresponding author
Ethics declarations
Conflict of Interest
The authors declare no conflict of interest. The funders had no role in the design of the study; in the collection, analyses, or interpretation of data; in the writing of the manuscript, or in the decision to publish the results.
Additional information
Publisher's Note
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
Rights and permissions
About this article
Cite this article
Wang, R., Deng, X., Meng, Y. et al. Application of Ultrasonic-Rebound Method in Fast Prediction of Rock Strength. Geotech Geol Eng 38, 5915–5924 (2020). https://doi.org/10.1007/s10706-020-01402-6
Received:
Accepted:
Published:
Issue Date:
DOI: https://doi.org/10.1007/s10706-020-01402-6