Development of an Underground Tunnels Detection Algorithm for Electrical Resistivity Tomography Based on Deep Learning
Source abstract
Abstract
Kinmen Island was in a state of combat readiness during the 1950s–1980s. It opened for tourism in 1992, when all troops withdrew from the island. Most military installations, such as bunkers, anti airborne piles, and underground tunnels, became deserted and disordered. The entries to numerous underground bunkers are closed or covered with weeds, creating dangerous spaces on the island. This study evaluates the feasibility of using Electrical Resistivity Tomography (ERT) to detect and discuss the location, size, and depth of underground tunnels. In order to discuss the reliability of the 2D-ERT result, this study built a numerical model to validate the correctness of in situ measured data. In addition, this study employed the artificial intelligence deep learning technique for reprocessing and predicting the ERT image and discussed using an artificial intelligence deep learning algorithm to enhance the image resolution and interpretation. A total of three 2D-ERT survey lines were implemented in this study. The results indicate that the three survey lines clearly show the tunnel location and shape. The numerical simulation results also indicate that using 2D-ERT to survey underground tunnels is highly feasible. Moreover, according to a series of studies in Multilayer Perceptron of deep learning, using deep learning can clearly show the tunnel location and path and effectively enhance the interpretation ability and resolution for 2D-ERT measurement results.
Source: crossref · Quality: baseline
Research context
OpenAlex topics: Geophysical and Geoelectrical Methods · Geophysical Methods and Applications · Seismic Waves and Analysis
SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.
Affiliations
Department of Civil Engineering and Engineering Management, National Quemoy University, Kinmen 89250, Taiwan
Department of Computer Science and Information Engineering, National Quemoy University, Kinmen 89250, Taiwan
References (54)
Show source-provided references
1. Chiang, B.W. (2005). Investigation and Research of Kinmen Wars Records, Kinmen National Park.
2. (2021, October 30). The Underground Tunnels Collapsed and Endangered the Houses, Kinmen Daily. Available online: https://www.chinatimes.com/realtimenews/20140523003816-260402?chdtv.
3. (2021, October 30). The Government Public Works Were Stopped Construction by Underground Tunnels during Excavation, Liberty Times, Available online: https://www.kmdn.gov.tw/1117/1271/1272/136247/.
4. (2021, October 30). The Government Public Works Were Found Ammunition Galleries during Excavation, Kinmen Daily, Available online: https://www.kmdn.gov.tw/1117/1271/1272/136098/?cprint=pt.
5. (2018). Raffaele Persico Salvatore Piro Neil Linford, Innovation in Near Surface Geophysics, Elsevier.
6. Applications and challenges of near surface geophysicals in geotechnical engineering
7. Application of geophysical methods in a dam project: Life cycle perspective and Taiwan experience10.1016/j.jappgeo.2018.07.012 ↗
8. Stokoe, K.H., Joh, S.H., and Woods, R.D. (2004, January 19–22). Some contribution of in situ geophysical measurements to solving geotechnical engineering problems. Proceedings of the 2nd International Geotechnical and Geophysical Site Characterization Conference, ISC-2, Porto, Portugal.
9. Geophysical Survey System, Inc. (1992). Traning Notes, GSSI Press.
10. Geophysical Survey System, Inc. (2003). RADAN for Windows Version 5.0 User’s Manual, GSSI Press.
11. GPR versus geoarchaeological findings in a complex archaeological site (Badia Pozzeveri, Italy)10.1002/arp.1561 ↗
12. Detecting the remaining structure foundation using ground penetrating radar: The outer wall of small east gate of Taiwan FU, Taiwan
13. GPR detection of inhomogeneities in concrete lining of underground tunnels10.1134/S1062739114010049 ↗
14. Comprehensive geophysical prediction and treatment measures of karst caves in deep buried tunnel10.1016/j.jappgeo.2015.03.019 ↗
15. Detection of underground cavities by combining gravity, magnetic and ground penetrating radar surveys: A case study from the Zaragoza area, NE Spain10.1007/s00254-007-0733-7 ↗
16. Karlovsek, J., Scheuermann, A., and Willimas, D.J. (2012, January 4–8). Investigation of voids and cavities in bored tunnels using GPR. Proceedings of the 2012 14th International Conference on Ground Penetrating Radar (GPR), Shanghai, China.10.1109/ICGPR.2012.6254916 ↗
17. GPR survey to confirm the location of ancient structures under the Valencian Cathedral (Spain)10.1016/S0926-9851(99)00056-7 ↗
18. The Use of Geophysical Prospections to Map Ancient Hydraulic Works: The Triglio Underground Aqueduct (Apulia, Southern Italy): GPR and ERT Survey on Ancient Hydraulic Works10.1002/arp.1541 ↗
19. The development of DC resistivity imaging techniques10.1016/S0098-3004(00)00160-6 ↗
20. Hung, Y.C., Chou, H.S., and Lin, C.P. (2020). Appraisal of the Spatial Resolution of 2D Electrical Resistivity Tomography for Geotechnical Investigation. Appl. Sci., 10.10.3390/app10124394 ↗
21. Case studies of electrical and electromagnetic methods applied to mapping active faults beneath the thick quaternary10.1016/S0013-7952(99)00132-5 ↗
22. The use of geophysical prospecting for imaging active faults in the Roer Graben, Belgium10.1190/1.1444925 ↗
23. A Case Study of Dipole-Dipole Resistivity for Geotechnical Engineering from the Ras en Naqab Area, South Jordan10.4133/JEEG8.1.31 ↗
24. High resolution images of the fault controlled High Agri Valley basin (Southern Italy) with deep and shallow electrical resistivity tomographies10.1016/j.pce.2003.12.002 ↗
25. Image processing of 2D resistivity data for imaging faults10.1016/j.jappgeo.2005.02.001 ↗
26. A Review of the Advantages and Limitations of Geophysical Investigations in Landslide Studies10.1155/2019/2983087 ↗
27. Application of a two dimensional electrical tomography technique for investigating landslides along the Amman–Dead Sea highway, Jordan10.1007/s00254-002-0543-x ↗
28. High resolution electrical imaging of the Varco d’Izzo earthflow (southern Italy)10.1016/j.jappgeo.2004.03.004 ↗
29. Chen, T.T., Hung, Y.C., Hsueh, M.W., Yeh, Y.H., and Weng, K.W. (2018). Evaluating the Application of Electrical Resistivity Tomography for Investigating Seawater Intrusion. Electronics, 7.10.3390/electronics7070107 ↗
30. DC resistivity monitoring of potassium permanganate injected to oxidize TCE in situ10.4133/JEEG4.3.135 ↗
31. Performance of 2D ERT in Investigation of Abnormal Seepage: A Case Study at the Hsin-Shan Earth Dam in Taiwan10.2113/JEEG19.2.101 ↗
32. Hung, Y.C., Chen, T.T., Tsai, T.F., and Chen, H.X. (2021). A Comprehensive Investigation on Abnormal Impoundment of Reservoirs—A Case Study of Qionglin Reservoir in Kinmen Island. Water, 13.10.3390/w13111463 ↗
33. Colucci, P., Darilek, G.T., Laine, D.L., and Binley, A. (1999, January 4–8). Locating Landfill Leaks Covered with Waste. Proceedings of the International Waste Management and Landfill Symposium, Sardinia 99, Cagliari, Italy.
34. Binley, A., Daily, W., and Ramirez, A. (1999, January 14). Detecting leaks from waste storage ponds using electrical tomographic methods. Proceedings of the 1st World Congress on Process Tomography, Buxton, UK.
35. Remote Monitoring of Leaks in Storage Tanks using Electrical Resistance Tomography: Application at the Hanford Site10.4133/JEEG9.1.11 ↗
36. 2D-3D resistivity and microgravity measurements for the detection of an ancient tunnel in the Lavrion area, Greece10.3997/1873-0604.2011024 ↗
37. Detection of underground tunnels using electrical resistivity and refraction seismic tomography methods
38. Electrical resistivity imaging in transmission between surface and underground tunnel for fault characterization10.1016/j.jappgeo.2016.03.004 ↗
39. Loke, M.H. (2004). Tutorial: 2-D and 3-D Electrical Imaging Surveys, Geotomo Software.10.1071/ASEG2004ab091 ↗
40. A survey on deep learning: Algorithms, techniques, and applications
41. 2D and 3D Electrical Resistivity Tomography (ERT) Investigation of Mineral Deposits in Amahor, Edo State, Nigeria
42. Three dimensional geoelectrical imaging of the subsurface structure of university of Benin-Edo state Nigeria
43. Resistivity Imaging at a Heterogeneous Two and Three Dimensional Electrical Remediation Site10.1190/1.1759453 ↗
44. Special 3D electric resistivity tomography (ERT) array applied to detect buried fractures on urban areas: San Antonio Tecómitl, Milpa Alta, México10.1016/S0016-7169(14)70076-5 ↗
45. 3D Electrical Resistivity Imaging (ERI) for subsurface evaluation in pre engineering construction site investigation10.1016/j.nrjag.2018.07.001 ↗
46. Geotomo Software 2002 (2021, October 30). RES2DMOD Ver. 3.01, Rapid 2D Resistivity forward Modelling Using the Finite Difference and Finite-Element Methods. Available online: https://www.geotomosoft.com/index.php.
47. Geotomo Software 2007 (2021, October 30). RES2DINV Ver. 3.56, Rapid 2D Resistivity and IP Inversion Using the Least Squares Method. Available online: https://www.geotomosoft.com/index.php.
48. Russell, S., and Norvig, P. (2021, October 30). Artificial Intelligence: A Modern Approach. Available online: https://storage.googleapis.com/pub-tools-public-publication-data/pdf/27702.pdf.
49. Rojas, R. (2013). Neural Networks: A Systematic Introduction, Springer Science & Business Media.
50. Nilsson, N.J. (2014). Principles of Artificial Intelligence, Morgan Kaufmann.
51. Deep learning10.1038/nature14539 ↗
52. Goodfellow, I., Bengio, Y., and Courville, A. (2016). Deep Learning, MIT Press.
53. Kingma, D.P., and Ba, J.L. (2015, January 7–9). Adam: A Method for Stochastic Optimization. Proceedings of the International Conference on Learning Representations, San Diego, CA, USA.
54. GANs Trained by a Two Time Scale Update Rule Converge to a Local Nash Equilibrium