Characteristic Parameters Extraction Method of Hidden Karst Cave from Borehole Radar Signal
Publication: International Journal of Geomechanics
Volume 20, Issue 8
Abstract
A hidden karst cave has a prominent influence on the design and construction of underground engineering. In order to improve the automatic identification accuracy of hidden karst cave areas and the acquisition accuracy of characteristic parameters in borehole radar signals, combined with the reflection characteristic relationship between radar electromagnetic waves and hidden karst caves, research methods on borehole radar image pre-processing and feature parameter extraction of hidden karst caves are carried out. First, based on the original signal of a borehole radar, the reflection characteristic relationship between the electromagnetic waves of the borehole radar and a hidden karst cave is established, and the geometric model of borehole radar detection of hidden karst caves is formed. Then, the reconstruction of borehole radar signals is realized by searching the peak position of Pmusic function combined with the subspace MUSIC method. Combining the continuity of hyperbola and the gray level difference of a nonreflective region, an improved variance method is proposed, which is more suitable for the actual borehole radar image segmentation. It realizes the suspected hidden karst cave inversion by setting a threshold of continuous pixels, a simultaneous gradient operator, and a maximum interspecific variance method. Finally, according to the geometric model of borehole radar detection, the energy-weighted fitting of a hyperbolic profile is carried out, and the improved Hough transform method is used to solve the multiple characteristic parameters of the hyperbolic model, so as to extract the characteristic parameters of the hidden cave from the borehole radar signal. The example analyzed proves that the method is feasible and accurate, which can provide important data support for underground engineering.
Get full access to this article
View all available purchase options and get full access to this article.
Acknowledgments
This work was supported by the State Key Program of National Natural Science of China (Grant No. 41731284), and the National Natural Science Foundation for the Youth of China (Grant No. 41902294).
References
Chen, D., C. Huang, and Y. Su. 2004. “An integrated method of statistical method and hough transform for GPR targets detection and location.” Acta Electron. Sinica 32 (9): 1468–1471.
Cheng, W. C., J. C. Ni, A. Arulrajah, and H.-W. Huang et al. 2018. “A simple approach for characterising tunnel bore conditions based upon pipe-jacking data.” Tunnelling Underground Space Technol. 71: 494–504. https://doi.org/10.1016/j.tust.2017.10.002.
Cheng, W. C., L. Wang, Z.-F. Xue, J. C. Ni, M. M. Rahman, and A. Arulrajah. 2019. “Lubrication performance of pipejacking in soft alluvial deposits.” Tunnelling Underground Space Technol. 91: 102991. https://doi.org/10.1016/j.tust.2019.102991.
Dong, L. J., W. Zou, X. B. Li, W. W. Shu, and Z. W. Wang. 2019. “Collaborative localization method using analytical and iterative solutions for microseismic/acoustic emission sources in the rockmass structure for underground mining.” Eng. Fract. Mech. 210: 95–112. https://doi.org/10.1016/j.engfracmech.2018.01.032.
Gurbuz, A. C., J. H. McClellan, and W. R. Scott, Jr. 2012. “Compressive sensing of underground structures using GPR.” Digital Signal Process. 22 (1): 66–73. https://doi.org/10.1016/j.dsp.2010.11.003.
Hu, Q. C., and L. J. Dong. 2019. “Acoustic emission source location and experimental verification for two-dimensional irregular complex structure.” IEEE Sens. J. 20 (5): 2679–2691. https://doi.org/10.1109/JSEN.2019.2954200.
Jiao, Y., W. Zhang, G. Ou, J. Zou, and G. Chen. 2019. “Review of the evolution and mitigation of the water-inrush disaster in drilling-and-blasting excavated deep-buried tunnels.” Hazard Control Tunnelling Underground Eng. 1 (1): 36–46.
Li, H., D.-h. Wang, Y.-j. Jiao, and Y. Zhou. 2011. “Application of borehole radar technology in hydrogeology and engineering geology.” Geotech. Invest. Surv. 39 (6): 85–89.
Li, S.-C. 2015. The theory and method of geological prediction for the disaster source of water and mud inrush in tunnels[M]. Beijing: China Science Publishing House.
Li, S. C., P. Lin, Z. H. Xu, L. P. Li, S. J. He, S. L. Zhao, and X. Huang et al. 2017. “Innovative method for the integral sliding stability analysis of filling media in karst caves and its applications in engineering.” Int. J. Geomech. 17 (12): 04017109. https://doi.org/10.1061/(ASCE)GM.1943-5622.0000979.
Li, S.-C., B. Liu, H.-f. Sun, L. C. Nie, S. H. Zhong, M. X. Su, X. Li, and Z. H. Xu. 2014. “State of art and trends of advanced geological prediction in tunnel construction.” Chin. J. Rock Mech. Eng. 33 (6): 1090–1113.
Liu, L.-b., and R.-y. Qian. 2015. “Ground penetrating radar: A critical tool in near-surface geophysics.” Chin. J. Geophys. 58 (8): 2606–2617. https://doi.org/10.6038/cjg20150802.
Liu, S. 2002. FDTD simulation of borehole radar and its application to electromagnetic well logging[D]. Sendai, Japan: Tohoku Univ.
Odendaal, J. W., E. Barnard, and C. W. I. Pistorius. 1994. “Two-dimensional superresolution radar imaging using the MUSIC algorithm.” IEEE Trans. Antennas Propag. 42 (10): 1386–1391. https://doi.org/10.1109/8.320744.
Perrotti, M., P. Lollino, N. L. Fazio, L. Pisano, G. Vessia, M. Parise, A. Fiore, and M. Luisi. 2018. “Finite element-based stability charts for underground cavities in soft calcarenites.” Int. J. Geomech. 18 (7): 04018071. https://doi.org/10.1061/(ASCE)GM.1943-5622.0001175.
Rappaport, C. M. 2007. “Accurate determination of underground GPR wavefront and B-Scan shape from above-ground point sources.” IEEE Trans. Geosci. Remote Sens. 45 (8): 2429–2434. https://doi.org/10.1109/TGRS.2007.901004.
Slob, E., M. Sato, and G. Olhoeft. 2010. “Surface and borehole ground-penetrating-radar developments.” Geophysics 75 (5): 75A103–75A120. https://doi.org/10.1190/1.3480619.
Su, R., Z.-h. Zong, R.-l. Ji, W. M. Chen, J. Xu, J. Wang, and Y. H. Guo. 2007. “Application of integrated borehole measurement techniques to hydrogeological characteristics evaluation of water-conductive fault.” Chin. J. Rock Mech. Eng. 26 (Supp. 2): 3866–3873.
Wang, J., C. Y. Wang, S. Hu, Q. Han, and Y. Wang. 2017. “Study on extraction method of structural plane parameters of borehole image.” Geotech. Mech. 38 (10): 3074–3080.
Wu, H., Y. Jiao, H. Li, and X. Zhang. 2008. “Technical method of ground penetrating radar for detecting grouting effect of air-raid shelter and its application.” Rock Soil Mech. 29 (Supp. 2): 307–310.
Xu, Z. H., J. Wu, S. C. Li, B. Zhang, and X. Huang. 2018. “Semianalytical solution to determine minimum safety thickness of rock resisting water inrush from filling-type karst caves.” Int. J. Geomech. 18 (2): 04017152. https://doi.org/10.1061/(ASCE)GM.1943-5622.0001071.
Zeng, Z.-f., S.-x. Liu, and X. Feng. 2010. The principle and application of ground penetrating radar[M]. Beijing: Publishing House of Electronics Industry.
Zhong, S. 2008. Borehole radar and digital camera dynamic survey technology on a number of key issues research[D]. Beijing: Graduate School of Chinese Academy of Sciences.
Zhong, S., C. Wang, X. Tang, and Y. Liu. 2017. “Response characteristics and forward modeling of borehole radar for planar unfavorable geological bodies.” High Tech Commun. 27 (1): 95–102.
Zhu, J. 2009. “Elliptic detection method using long axis estimation.” Comput. Syst. Appl. 12: 79–82.
Information & Authors
Information
Published In
Copyright
© 2020 American Society of Civil Engineers.
History
Received: Aug 18, 2019
Accepted: Jan 30, 2020
Published online: May 21, 2020
Published in print: Aug 1, 2020
Discussion open until: Oct 21, 2020
Authors
Metrics & Citations
Metrics
Citations
Download citation
If you have the appropriate software installed, you can download article citation data to the citation manager of your choice. Simply select your manager software from the list below and click Download.