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Tytuł artykułu

The new approach of using image and range based methods for quality control of dimension stone

Autorzy
Treść / Zawartość
Identyfikatory
Warianty tytułu
Języki publikacji
EN
Abstrakty
EN
The basis for the quality control of commodity dimension stone blocks for mining industry is the study of fracturing. The identification of fracturing in rock masses is one of the most important aspects in rock mass modelling. Traditional methods for determination properties of fracturing are difficult and hazardous. This paper describes a new approach of fracturing identification, based on image and range data, which realized by image processing and special software. In this article describes a method using new computer algorithms that allow for automated identification and calculation of fracturing parameters. Different digital filters for image processing and mathematical dependences are analyzed. The digital imaging technique has the potential for being used in real time applications. The purpose of this paper is the accurate and fast mapping of fracturing in some walls of the Bukinsky gabbro deposit.
Rocznik
Tom
Strony
66--77
Opis fizyczny
Bibliogr. 20 poz., rys.
Twórcy
autor
  • Department of Mine Surveying, Zhytomyr State Technological University, St. Chudnivska 103, 10005, Zhytomyr, Ukraine
Bibliografia
  • [1] Canny, J. (1986). A computational approach to edge detection. IEEE Transactions on Pattern Analysis and Machine Intelligence, 8(6), pp. 679-698.
  • [2] Coggan, J.S., Wetherelt, A., Gwynn, X.P. & Flynn, Z.N. (2007). Comparison of hand-mapping with remote data capture systems for effective rock mass characterization. 11th Congress of the International Society for Rock Mechanics, 1, pp. 201-206.
  • [3] Dare, P.M., Hanley, H.B., Fraser, C.S., Riedel, B. & Niemeier, W. (2002). An operational application of automatic feature extraction the measurement of cracks in concrete structures. Photogrammetric Record, 17(99), pp. 453-464.
  • [4] Delis P., Wojtkowska M., Nerc P., Ewiak I. & Lada A. (2016). Integration of geodata in documenting castle ruins. XXIII ISPRS CONGRESS, COMMISSION III. International Archives of the Photogrammetry Remote Sensing and Spatial Information Sciences, 41(B3), pp. 345-349. doi:10.5194/isprsarchives-XLI-B3-345-2016.
  • [5] Feng, Q.H. & Roshoff, K. (2004). In-Situ Mapping and Documentation of Rock Faces Using a Full Coverage 3D Laser Scanning Technique. International Journal of Rock Mechanics and Mining Science, 41(1), pp. 1-6.
  • [6] Gonzalez, R.C. & Woods, R.E. (2008). Digital image processing (3rd edition). Upper Saddle River, NJ: Prentice-Hall.
  • [7] González-Aguilera, D., López-Fernández, L., Rodriguez-Gonzalvez, P., Guerrero, D., Hernandez-Lopez, D., Remondino, F., Menna, F., Nocerino, E., Toschi, I., Ballabeni, A. & Gaiani, M. (2016). Development of an all-purpose free photogrammetric tool. The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, 41(B6), pp. 31-38. DOI: 10.5194/isprsarchives-XLI-B6-31-2016.
  • [8] Haneberg, W.C. (2008). Using close range terrestrial digital photogrammetry for 3-D rock slope modeling and discontinuity mapping in the United States. Bull. Eng. Geol. Environ, 67(4), pp. 457-469.
  • [9] Jing, L. (2003). A review of techniques, advances and outstanding issues in numerical modelling for rock mechanics and rock engineering. International Journal of Rock Mechanics and Mining Sciences, 40(3), pp. 283-353.
  • [10] Kemeny, J., Mofya, E., Holmlund, J. & Ahlgren, S. (2002). Digital imaging for rock mass characterization. Proceedings of the 2nd Annual Conference on the Application of Geophysical and NDT Methodologies To Transportation Facilities and Infrastructure (Geophysics 2002), Los Angeles.
  • [11] Kemeny, J. & Post, R. (2003). Estimating three-dimensional rock discontinuity orientation from digital images of fracture traces. Computers and Geosciences, 29 (1), pp. 65-77. DOI: 10.1016/S0098-3004(02)00106-1.
  • [12] Lemy, F. & Hadjigeorgiou, J. (2003). Discontinuity trace map construction using photographs of rock exposures. International Journal of Rock Mechanics and Mining Sciences, 40(6), pp. 903-917.
  • [13] Mohebbi, M., Yarahmadi Bafghi, A.R., Fatehi Marji M. & Gholamnejad J. (2017). Rock mass structural data analysis using image processing techniques (Case study: Choghart iron ore mine northern slopes). Journal of Mining & Environment, 8(1), pp. 61-74. DOI: 10.22044/jme.2016.629.
  • [14] Poropat, G.V. (2001). New methods for mapping the structure of rock masses. CSIRO Exploration and Mining, paper for Explo 2001, pp. 253-260.
  • [15] Priest, S.D. (1993). Discontinuity analysis for rock engineering. Chapman & Hall, London, 473.
  • [16] Sobolevskyi, R., Zuievska, N., Korobiichuk, V., Tolkach O. & Kotenko V. (2016). Cluster analysis of fracturing in the deposits of decorative stone for the optimization of the process of quality control of block raw material. Eastern-European Journal of Enterprise Technologies, 5(83), pp. 21-29. DOI: 10.15587/1729-4061.2016.80652.
  • [17] Turanboy, A. & Ülker, E. (2010). A new approach to rapid 3D mapping of rock mass structure. Geotechnical Engineering, 163(6), pp. 321-331. DOI: 10.1680/geng.2010.163.6.321.
  • [18] Wang, P. & Huang, H. (2010). Comparison analysis on present image-based crack detection methods in concrete structures. 2010 3rd International Congress on Image and Signal Processing (CISP2010), 5, pp. 2530-2533.
  • [19] Yamaguchi, T. & Hashimoto, S. (2009). Practical image measurement of crack width for real concrete structure. Electronics and Communications in Japan, 92(10), pp. 605-614.
  • [20] Zawieska, D. & Markiewicz, J. (2015). Utilisation of laser scanning technology and digital images for measurements of industrial objects - a case study. Reports on Geodesy and Geoinformatics, 98(1). DOI: 10.2478/rgg-2015-0003.
Uwagi
PL
Opracowanie ze środków MNiSW w ramach umowy 812/P-DUN/2016 na działalność upowszechniającą naukę (zadania 2017).
Typ dokumentu
Bibliografia
Identyfikator YADDA
bwmeta1.element.baztech-277d309f-68b1-4572-8109-ec1531eb6b16
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