A review of laser scanning for geological and geotechnical applications in underground mining

Laser scanning can provide timely assessments of mine sites despite adverse challenges in the operational environment.Although there are several published articles on laser scanning,there is a need to review them in the context of underground mining applications.To this end,a holistic review of laser scanning is presented including progress in 3D scanning systems,data capture/processing techniques and primary applications in underground mines.Laser scanning technology has advanced significantly in terms of mobility and mapping,but there are constraints in coherent and consistent data collection at certain mines due to feature deficiency,dynamics,and environmental influences such as dust and water.Studies suggest that laser scanning has matured over the years for change detection,clearance measurements and structure mapping applications.However,there is scope for improvements in lithology identification,surface parameter measurements,logistic tracking and autonomous navigation.Laser scanning has the potential to provide real-time solutions but the lack of infrastructure in underground mines for data transfer,geodetic networking and processing capacity remain limiting factors.Nevertheless,laser scanners are becoming an integral part of mine automation thanks to their affordability,accuracy and mobility,which should support their widespread usage in years to come.

Spoil characterisation using UAV-based optical remote sensing in coal mine dumps

The structural integrity of mine dumps is crucial for mining operations to avoid adverse impacts on the triple bottom-line.Routine temporal assessments of coal mine dumps are a compliant requirement to ensure design reconciliation as spoil off-loading continues over time.Generally,the conventional in-situ coal spoil characterisation is inefficient,laborious,hazardous,and prone to experts'observation biases.To this end,this study explores a novel approach to develop automated coal spoil characterisation using unmanned aerial vehicle(UAV)based optical remote sensing.The textural and spectral properties of the high-resolution UAV images were utilised to derive lithology and geotechnical parameters(i.e.,fabric structure and relative density/consistency)in the proposed workflow.The raw images were converted to an orthomosaic using structure from motion aided processing.Then,structural descriptors were computed per pixel to enhance feature modalities of the spoil materials.Finally,machine learning algorithms were employed with ground truth from experts as training and testing data to characterise spoil rapidly with minimal human intervention.The characterisation accuracies achieved from the proposed approach manifest a digital solution to address the limitations in the conventional characterisation approach.

A robust approach to identify roof bolts in 3D point cloud data captured from a mobile laser scanner

Roof bolts such as rock bolts and cable bolts provide structural support in underground mines.Frequent assessment of these support structures is critical to maintain roof stability and minimise safety risks in underground environments.This study proposes a robust workflow to classify roof bolts in 3 D point cloud data and to generate maps of roof bolt density and spacing.The workflow was evaluated for identifying roof bolts in an underground coal mine with suboptimal lighting and global navigation satellite system(GNSS)signals not available.The approach is based on supervised classification using the multi-scale Canupo classifier coupled with a random sample consensus(RANSAC)shape detection algorithm to provide robust roof bolt identification.The issue of sparseness in point cloud data has been addressed through upsampling by using a moving least squares method.The accuracy of roof bolt identification was measured by correct identification of roof bolts(true positives),unidentified roof bolts(false negatives),and falsely identified roof bolts(false positives)using correctness,completeness,and quality metrics.The proposed workflow achieved correct identification of 89.27%of the roof bolts present in the test area.However,considering the false positives and false negatives,the overall quality metric was reduced to 78.54%.

An investigation of machine learning techniques to estimate minimum horizontal stress magnitude from borehole breakout

Borehole breakout is a widely utilised phenomenon in horizontal stress orientation determination,and breakout geometrical parameters,such as width and depth,have been used to estimate both horizontal stress magnitudes.However,the accuracy of minimum horizontal stress estimation from borehole breakout remains relatively low in comparison to maximum horizontal stress estimation.This paper aims to compare and improve the minimum horizontal stress estimation via a number of machine learning(ML)regression techniques,including parametric and non-parametric models,which have rarely been explored.ML models were trained based on 79 laboratory data from published literature and validated against 23 field data.A systematic bias was observed in the prediction for the validation dataset whenever the horizontal stress value exceeded the maximum value in the training data.Nevertheless,the pattern was captured,and the removal of systematic bias showed that the artificial neural network is capable of predicting the minimum horizontal stress with an average error rate of 10.16%and a root mean square error of 3.87 MPa when compared to actual values obtained through conventional in-situ measurement techniques.This is a meaningful improvement considering the importance of in-situ stress knowledge for underground operations and the availability of borehole breakout data.

Ayurveda perspective and global scenario of Wet cupping therapy-a comprehensive review

Wet cupping is a simple and minor procedure practiced in Ayurveda and various traditional medicine system worldwide.In Ayurveda wet cupping therapy is practiced under the scope of Raktamo Kshana(therapeutic bloodletting)which is adopted to remove vitiated Rakta(blood).The present work is aimed to explore the wet cupping therapy from Ayurveda perspective along with global scenario.In this review,classical Ayurveda text and PubMed,Cochrane library,science direct,Google scholar and DHARA database were scrutinized for worldwide work on wet cupping therapy.The Ayurveda science can utilize these researches in completing its lost knowledge and also provide integrative effort in re-validation and enrichment of WCT which are required at large for greater benefit of the mankind.The method of WCT application,principles,indications,contraindications,complications and probable mode of action from Ayurveda perspective and global scenario were introduced and summarized.