Should the Use of Rock Quality Designation Be Discontinued in the Rock Mass Rating System?

Chen, Qingfa; Yin, Tingchang

doi:10.1007/s00603-018-1607-x

Cited by 8 publications

(3 citation statements)

References 17 publications

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“…Едноставностa и ниската цена на спроведување на RQD индексот, резултира со примена во широк спектар на области во кои како главни влегуваат рударството и изработката на тунели. Битно е да се напомене дека RQD индексот е под влијание на голем број добро познати фактори и ограничувања кои придонесуваат добиените вредности да се користат со претпазливост [6][7][8].…”

Section: воведunclassified

Methodology for Automated Approach in Determining the Rock Quality Designation (Rqd) Index From Drill Core Photographs

Adjiski¹

2021

NRT

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Издавачки совет Проф. д-р Блажо Боев Проф. д-р Зоран Десподов Проф. д-р Лилјана Колева -Гудева Проф. д-р Зоран Панов Проф. д-р Борис Крстев Проф. д-р Мирјана Голомеова Проф. д-р Благој Голомеов Проф. д-р Дејан Мираковски Проф. д-р Тодор Серафимовски Проф. д-р Војо Мирчовски Проф. д-р Тена Шијакова -Иванова Проф. д-р Соња Лепиткова Проф. д-р Гоше Петров Проф. д-р Кимет Фетаху, (Политехнички универзитет во Тирана, Р.Албанија) Проф. д-р Ивајло Копрев, (МГУ Софија, Р. Бугарија) Проф. д-р Никола Лилиќ, (Универзитет во Белград, Р. Србија) Проф. д-р Јоже Кортник Универзитет во Љубљана, Р. Словенија Проф. д-р Даниела Марасова, (Технички универзитет во Кошице, Р. Словачка) Редакциски одбор Проф. д-р Зоран Десподов Проф. д-р Зоран Панов Проф. д-р Борис Крстев Проф. д-р Мирјана Голомеова Проф. д-р Благој Голомеов Проф. д-р Дејан Мираковски Проф. д-р Николинка Донева Проф. д-р Марија Хаџи -Николова Главен и одговорен уредник Проф. д-р Афродита Зенделска Јазично уредување Весна Ристова (македонски јазик) Техничко уредување Кире Зафиров Редакција и администрација Универзитет "Гоце Делчев" -Штип Факултет за природни и технички науки ул. "Гоце Делчев" 89, Штип Република Северна Македонија URL:

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Section: воведunclassified

Methodology for Automated Approach in Determining the Rock Quality Designation (Rqd) Index From Drill Core Photographs

Adjiski¹

2021

NRT

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“…In extension theory, a correlation function is used to indicate the extent to which an element has a certain property. In the following, according to the definition of extension theory, a formula for calculating the correlation degree [30,31,32,33] of each evaluation index is given. kjfalse(xifalse)={ρfalse(xi,b,X0false)ρfalse(xi,b,Xfalse)−ρfalse(xi,b,X0false)xi∉X0ρfalse(xi,b,x0false)ρfalse(xi,b,Xfalse)−ρfalse(xi,b,X0false)+amji−bmjixi∈X0ρfalse(xj,b,X0false)amji−bmjiρfalse(xi,b,X0false)=ρfalse(x…”

Section: Stability Evaluation Model Of Surrounding Rock In Deep MImentioning

confidence: 99%

Risk Analysis and Extension Assessment for the Stability of Surrounding Rock in Deep Coal Roadway

Gao

Huang

Chang

et al. 2019

IJERPH

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In order to evaluate the surrounding rock stability of deep roadways, the diversity of accident hazard sources in deep coal mining is statistically analyzed. To conduct an effective evaluation, first, the risk analysis of the factors affecting the rock mass accidents is carried out, and the comprehensive safety index system of rock accidents in deep mine roadway is established. Further, combining the theory of hazard sources with the extension method, a matter–element model for the risk assessment of rock mass accidents in deep roadway is established. Finally, the hazard sources for the surrounding rock stability of deep roadway in the E-Zhuang coal mine of Xinwen Ming area are evaluated. The results show that the risk grade of the surrounding rock for deep roadways in E-Zhuang coal mine is “B”, which is generally safe, the human factors and organizational management factors are relatively safe, and some suggestions for improvement are put forward.

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“…Rock quality designation (RQD) is a key element in rock mass classification, and an important input parameter in widely used rating systems, such as the rock mass rating (RMR) and Q values (Bieniawski 1973(Bieniawski , 1989Barton et al 1974;Lemy et al 2001;Chen and Yin 2019). RQD was introduced by Deere et al (1967) as a modified core recovery percentage, and is commonly used in mining and geotechnical engineering.…”

Section: Introductionmentioning

confidence: 99%

Automated Rock Quality Designation Using Convolutional Neural Networks

Alzubaidi

Mostaghimi

et al. 2022

Rock Mech Rock Eng

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Mineral and hydrocarbon exploration relies heavily on geological and geotechnical information extracted from drill cores. Traditional drill-core characterization is based purely on the subjective expertise of a geologist. New technologies can provide automatic mineral analysis and high-resolution drill core images in a non-destructive manner. However, automated rock mass characterization presents a significant challenge due to its lack of generalization and robustness. To date, the automated estimation of rock quality designation (RQD), a key parameter for rock mass classification, is based mostly on digital image processing techniques with significant user biases. Alternatively, we propose using computer vision and machine learning-based algorithms for drill core characterization using drill core images to determine the RQD. A convolutional neural network (CNN) is used to detect and classify intact and non-intact cores, and to filter out empty tray areas and non-rock objects present in the core trays. The model calculates the length of the detected intact cores and estimates the RQD. We train the CNN model with thousands of sandstone core images from different drill holes in South Australia. The proposed method is tested on 540 sandstone core rows and 90 limestone core rows (~ 1 m each), which produces average error rates of 2.58% and 3.17%, respectively.

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Should the Use of Rock Quality Designation Be Discontinued in the Rock Mass Rating System?

Cited by 8 publications

References 17 publications

Methodology for Automated Approach in Determining the Rock Quality Designation (Rqd) Index From Drill Core Photographs

Methodology for Automated Approach in Determining the Rock Quality Designation (Rqd) Index From Drill Core Photographs

Risk Analysis and Extension Assessment for the Stability of Surrounding Rock in Deep Coal Roadway

Automated Rock Quality Designation Using Convolutional Neural Networks

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