FFKM: A Software for Automatic Discontinuity Set Identification and Stereographic Projection Analysis
Discontinuities significantly influence the mechanical and hydraulic behavior of rock masses. Identifying and classifying discontinuities into sets with similar orientations is a crucial task in geotechnical engineering and mining. The most common method for grouping discontinuities involves the vis...
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| Vydáno v: | Revista minelor (Bucharest, Romania : 1990) Ročník 31; číslo 2; s. 56 - 65 |
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| Hlavní autoři: | , , , |
| Médium: | Journal Article |
| Jazyk: | angličtina |
| Vydáno: |
Petrosani
De Gruyter Brill Sp. z o.o., Paradigm Publishing Services
01.06.2025
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| Témata: | |
| ISSN: | 1220-2053, 2247-8590 |
| On-line přístup: | Získat plný text |
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| Shrnutí: | Discontinuities significantly influence the mechanical and hydraulic behavior of rock masses. Identifying and classifying discontinuities into sets with similar orientations is a crucial task in geotechnical engineering and mining. The most common method for grouping discontinuities involves the visual interpretation of stereographic projection maps. However, this method is limited by subjective factors such as personal experience, the size of the counting circle, variations in the frequency of discontinuity sets, outliers, and overlap. To overcome these limitations, we propose applying the Fuzzy K-Means algorithm based on the Fisher distribution (FFKM), implemented in Scilab as open-source software. This software automatically identifies discontinuity sets and calculates their statistical characteristics. Additionally, it determines the optimal number of sets and generates stereographic projections of the results. To demonstrate the effectiveness of FFKM, it was employed to identify fracture sets in an operational slope in an open-pit iron mine located in the Quadrilátero Ferrífero region in Brazil. The FFKM consistently identified the number of fracture sets and classified them according to the field data, providing reliable and objective results. |
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| Bibliografie: | ObjectType-Article-1 SourceType-Scholarly Journals-1 ObjectType-Feature-2 content type line 14 |
| ISSN: | 1220-2053 2247-8590 |
| DOI: | 10.2478/minrv-2025-0018 |