Conference Proceedings
Fourth International Future Mining Conference 2019
Conference Proceedings
Fourth International Future Mining Conference 2019
Automated rock quality designation (RQD) estimation from digital images of drill cores using convolutional neural networks
Rock Quality Designation (RQD) is an index of rock quality commonly used in mining and geotechnical engineering. It is defined as the percentage of solid core fragments longer than 10cm within the total core run, eliminating fractured and weak rocks. RQD is a key element in rock mass classification, and an important parameter in widely used systems such as Rock Mass Rating (RMR) and Rock Tunnelling quality (Q-system). Traditionally, RQD is measured manually by the visual observation of rock core. Often, this routine is not sufficiently diligent due to limited number of core trays that one geologist can realistically process, and time constraints in core logging procedures. In addition, the RQD value characterised by the geologist may also be biased based on individuals experience.
CITATION: Al-zubaidi, F, Mostaghimi, P, Si, G, Swietojanski, P and Armstrong, R T, 2019. Automated rock quality designation (RQD) estimation from digital images of drill cores using convolutional neural networks, in Proceedings Future Mining 2019, pp 57 (The Australasian Institute of Mining and Metallurgy: Melbourne).
CITATION: Al-zubaidi, F, Mostaghimi, P, Si, G, Swietojanski, P and Armstrong, R T, 2019. Automated rock quality designation (RQD) estimation from digital images of drill cores using convolutional neural networks, in Proceedings Future Mining 2019, pp 57 (The Australasian Institute of Mining and Metallurgy: Melbourne).
Contributor(s):
F Al-zubaidi, P Mostaghimi, G Si, P Swietojanski, R T Armstrong
-
Automated rock quality designation (RQD) estimation from digital images of drill cores using convolutional neural networksPDFThis product is exclusive to Digital library subscription
-
Automated rock quality designation (RQD) estimation from digital images of drill cores using convolutional neural networksPDFNormal price $16.50Member price from $0.00
Fees above are GST inclusive
PD Hours
Approved activity
- Published: 2019
- PDF Size: 0.166 Mb.
- Unique ID: P201907001