Skip to main content
Log in

Development of a 2D and 3D computational algorithm for discontinuity structural geometry identification by artificial intelligence based on image processing techniques

  • Original Paper
  • Published:
Bulletin of Engineering Geology and the Environment Aims and scope Submit manuscript

Abstract

Block geometry is commonly the most important feature determining the behaviour of a rock mass and directly controls the structural instability in underground openings or surface cuttings. Various methods are used to estimate block geometry and to perform a block survey, and these are standardly divided into empirical-based methods (e.g. spot mapping, linear mapping, areal mapping) and computer-based methods (e.g. laser scanning, image processing, digital image mapping). Empirical approaches are associated with effective features as well as with a number of errors; however, the latter can be covered by artificial intelligence (AI) techniques. The combination of image processing and areal mapping have led to geometric block estimation in two-dimensional (2D) and three-dimensional (3D) spaces; these approaches can be widely used in stability analysis, dimension stone extraction, excavations, open pit mining design and the delineation of blasting patterns for dimension stone extraction. Therefore, the application of an approach that allows both the modelling and production of rock blocks based on their actual status with qualified accuracy and speed are both worthwhile and necessary. In this study, to estimate the shape and block dimension utilized, we used the algorithm based on the AI image processing technique for rock mass structural detection and for rock block definition in 2D and 3D space obtained with the Mathematica software package. The algorithm, by categorizing the discontinuities in two groups (opened and closed), which represents the main and the secondary discontinuities, can identify the emplacement and shape of rock blocks.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Subscribe and save

Springer+ Basic
EUR 32.99 /Month
  • Get 10 units per month
  • Download Article/Chapter or Ebook
  • 1 Unit = 1 Article or 1 Chapter
  • Cancel anytime
Subscribe now

Buy Now

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6
Fig. 7
Fig. 8
Fig. 9
Fig. 10
Fig. 11
Fig. 12
Fig. 13
Fig. 14
Fig. 15
Fig. 16
Fig. 17
Fig. 18
Fig. 19

Similar content being viewed by others

References

  • Alejano LR, Pons B, Bastante FG, Alonso E, Stockhausen HW (2007) Slope geometry design as a means for controlling rockfalls in quarries. Int J Rock Mech Min Sci 44(6):903–921

    Article  Google Scholar 

  • Azarafza M, Yarahmadi-Bafghi AR, Asghari-Kaljahi E, Bahmannia GR, Moshrefy-Far MR (2013) Stability analysis of jointed rock slopes using key block method (case study: gas flare site in 6, 7 and 8 phases of south pars gas complex). J Geotch Geol 9(3):169–185 (in Persian)

    Google Scholar 

  • Azarafza M, Asghari-Kaljahi E, Akgün H (2017a) Numerical modeling of discontinuous rock slope utilizing the 3DDGM (three dimensional discontinuity geometrical modeling) method. Bull of Eng Geol Environ 76:989–1007

    Article  Google Scholar 

  • Azarafza M, Asghari-Kaljahi E, Akgün H (2017b) Assessment of discontinuous rock slope stability with block theory and numerical modeling: a case study for the South Pars Gas Complex, Assalouyeh, Iran. Environ Earth Sci 76(11):397

    Article  Google Scholar 

  • Azarafza M, Feizi-Derakhshi MR, Azarafza M (2017c) Computer modeling of crack propagation in concrete retaining walls: a case study. Comput Concrete (CAC) 19(5):509–514.

    Article  Google Scholar 

  • Bozzini M, Lenarduzzi L, Rossini M (2014) Non-regular surface approximation. Math Methods Curv Surf 8177:68–87

    Article  Google Scholar 

  • Brady BHG, Brown ET (2010) Rock mechanics: for underground mining, 3rd edn. Springer SBM, Berlin Heidelberg New York

  • Cacciari PP, Futai MM (2016) Mapping and characterization of rock discontinuities in a tunnel using 3D terrestrial laser scanning. Bull Eng Geol Environ 75(1):223–237

    Article  Google Scholar 

  • Cao F (2000) Geometric curve evolution and image processing. Springer-Verlag, Berlin Heidelberg New York

    Google Scholar 

  • Gonzalez RC, Woods RE (2002) Digital image processing. Prentice Hall, Upper Saddle River

  • Goodman RE (1976) Methods of geological engineering in discontinuous rocks. West, St. Paul

  • Goodman RE (1989) Introduction to rock mechanics. Wiley & Sons, New York

  • Goodman RE, Shi G (1985) Block theory and its application to rock engineering. Prentice-Hall, Upper Saddle River

    Google Scholar 

  • Gonzalez RC, Woods RE, Steven L (2010) Digital image processing using MATLAB, 2nd edn. McGraw-Hill Education, New York

  • Hamdi E, du Mouza J (2005) A methodology for rock mass characterization and classification to improve blast results. Int J Rock Mech Min Sci 42(2):177–194

    Article  Google Scholar 

  • Hudson JA, Harrison JP (1997) Engineering rock mechanics—an introduction to the principles. Elsevier Science, Amsterdam

  • Jaeger JC, Cook NG, Zimmerman R (2009) Fundamentals of rock mechanics. Wiley, Oxford

    Google Scholar 

  • Jain R, Kasturi R, Schunck BG (1995) Machine vision. McGraw-Hill, New York

  • MathWorks (2014) MATLAB, Version R2014b. MathWorks Inc., Natick

  • Nikoobakht S, Ghazifard A, Azarafza M (2016) Stability analysis of sliding wedges in exit portal of Golab 2 tunnel. In: 34th National and the 2nd International geosciences congress of Iran (in Persian)

  • Palmstrom A (1982) The volumetric joint count—a useful and simple measure of the degree of rock mass jointing. In: Proc IAEG Congress. New Delhi, India

  • Palmstrom A (1996a) The weighted joint density method leads to improved characterization of jointing. In: Int Conference Recent Advances in Tunnelling Technology. New Delhi, India

  • Palmstrom A (1996b) Characterizing rock masses by the RMi for use in practical rock engineering. Part 1: the development if the rock mass index (RMi). Tunn Undergr Space Technol 11(2):175–188

    Article  Google Scholar 

  • Palmstrom A (2000) Block size and block size distribution. In: Proc GeoEng2000 Conference. 18–24 November 2000. Melbourne

  • Palmstrom A (2005) Measurements and correlations between block size and rock quality designation (RQD). Tunn Undergr Space Technol 20(4):362–377

  • Porsani JL, Sauck WA, Junior AO (2006) GPR for mapping fractures and as a guide for the extraction of ornamental granite from a quarry: a case study from southern Brazil. J Appl Geophys 58(3):177–187

  • Priest S (1993) Discontinuity analysis for rock engineering. Chapman & Hall, London

  • Prost GL (2013) Remote sensing for geoscientists: image analysis and integration, 3rd edn. CRC press, Baton Rouge

  • Pusch R (1995) Rock mechanics on a geological base. Academic Press, New York

  • Saliu MA, Idowu KA (2014) Investigating the effect of fracture on rock fragmentation efficiency: a case study of Kopec granite quarries, south western, Nigeria. J Earth Sci Geotech Eng 4(4):53–69

    Google Scholar 

  • Ulusay R (2015) The ISRM suggested methods for rock characterization, testing and monitoring: 2007–2014. Springer SBM, Basel

  • Wolfram S (2003) The Mathematica book, 5th edn. Wolfram Media/Cambridge University Press, Cambridge

  • Yarahmadi R, Bagherpour R, Sousa LMO, Taherian S (2015) How to determine the appropriate methods to identify the geometry of in situ rock blocks in dimension stones. Environ Earth Sci 74:6779–6790

    Article  Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Akbar Ghazifard.

Ethics declarations

The authors declare that they have no conflicts of interest.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Azarafza, M., Ghazifard, A., Akgün, H. et al. Development of a 2D and 3D computational algorithm for discontinuity structural geometry identification by artificial intelligence based on image processing techniques. Bull Eng Geol Environ 78, 3371–3383 (2019). https://doi.org/10.1007/s10064-018-1298-2

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s10064-018-1298-2

Keywords

Navigation