978 resultados para Mine timbering.


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This paper describes a series of trials that were done at an underground mine in New South Wales, Australia. Experimental results are presented from the data obtained during the field trials and suitable sensor suites for an autonomous mining vehicle navigation system are evaluated.

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This paper reviews the state-of-the art in the automation of underground truck haulage. Past attemps at automating LHDs and haul trucks are described and their particular strengths and weaknesses are listed. We argue that the simple auto-tram...

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Draglines are very large machines that are used to remove overburden in open-cut coal mines. This paper outlines the design of a computer control system to implement an automated swing cycle on a production dragline. Subsystems and sensors have been developed to satisfy the constraints imposed by the task, the harsh operating environment and the mine's production requirements.

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Dragline Swing to Dump Automation By Peter Corke, CSIRO Manufacturing Technology/CRC for Mining Technology and Equipment (CMTE) Peter Corke presented a case study of a project to automate the dragline swing to dump operation. The project is funded by ACARP, BHP Coal, Pacific Coal and the CMTE and is being carried out on a dragline at Pacific Coal's Meandu mine near Brisbane. Corke began by highlighting that the minerals industry makes extensive use of large, mechanised machines. However, unlike other industries, mining has not adopted automation and most machines are controlled by human operators on board the machine itself. Choosing an automation target The dragline automation was chosen because: ò draglines are one of the biggest capital assets in a mine; ò performance between operators vary significantly, so improved capital utilisation is possible; ò the dragline is often the bottleneck in production; ò a large part of the operation cycle is spent swinging from dig to dump; and ò it is technically feasible. There has been a history of drag line automation projects, none with great success.

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The Field and Service Robotics (FSR) conference is a single track conference with a specific focus on field and service applications of robotics technology. The goal of FSR is to report and encourage the development of field and service robotics. These are non-factory robots, typically mobile, that must operate in complex and dynamic environments. Typical field robotics applications include mining, agriculture, building and construction, forestry, cargo handling and so on. Field robots may operate on the ground (of Earth or planets), under the ground, underwater, in the air or in space. Service robots are those that work closely with humans, importantly the elderly and sick, to help them with their lives. The first FSR conference was held in Canberra, Australia, in 1997. Since then the meeting has been held every 2 years in Asia, America, Europe and Australia. It has been held in Canberra, Australia (1997), Pittsburgh, USA (1999), Helsinki, Finland (2001), Mount Fuji, Japan (2003), Port Douglas, Australia (2005), Chamonix, France (2007), Cambridge, USA (2009), Sendai, Japan (2012) and most recently in Brisbane, Australia (2013). This year we had 54 submissions of which 36 were selected for oral presentation. The organisers would like to thank the international committee for their invaluable contribution in the review process ensuring the overall quality of contributions. The organising committee would also like to thank Ben Upcroft, Felipe Gonzalez and Aaron McFadyen for helping with the organisation and proceedings. and proceedings. The conference was sponsored by the Australian Robotics and Automation Association (ARAA), CSIRO, Queensland University of Technology (QUT), Defence Science and Technology Organisation Australia (DSTO) and the Rio Tinto Centre for Mine Automation, University of Sydney.

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This paper presents visual detection and classification of light vehicles and personnel on a mine site.We capitalise on the rapid advances of ConvNet based object recognition but highlight that a naive black box approach results in a significant number of false positives. In particular, the lack of domain specific training data and the unique landscape in a mine site causes a high rate of errors. We exploit the abundance of background-only images to train a k-means classifier to complement the ConvNet. Furthermore, localisation of objects of interest and a reduction in computation is enabled through region proposals. Our system is tested on over 10km of real mine site data and we were able to detect both light vehicles and personnel. We show that the introduction of our background model can reduce the false positive rate by an order of magnitude.

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Raman and infrared spectra of three well-defined turquoise samples, CuAl6(PO4)4(OH)8·4H2O, from Lavender Pit, Bisbee, Cochise county, Arizona; Kouroudaiko mine, Faleme river, Senegal and Lynch Station, Virginia were studied, interpreted and compared. Observed Raman and infrared bands were assigned to the stretching and bending vibrations of phosphate tetrahedra, water molecules and hydroxyl ions. Approximate O–H⋯O hydrogen bond lengths were inferred from the Raman and infrared spectra. No Raman and infrared bands attributable to the stretching and bending vibrations of (PO3OH)2− units were observed.

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The largest Neoarchean gold deposits in the world-class St Ives Goldfield, Western Australia, occur in an area known as the Argo-Junction region (e.g. Junction, Argo and Athena). Why this region is so well endowed with large deposits compared with other parts of the St Ives Goldfield is currently unclear, because gold deposits at St Ives are hosted by a variety of lithologic units and were formed during at least three different deformational events. This paper presents an investigation into the stratigraphic architecture and evolution of the Argo-Junction region to assess its implications for gold metallogenesis. The results show that the region's stratigraphy may be subdivided into five regionally correlatable packages: mafic lavas of the Paringa Basalt; contemporaneously resedimented feldspar-rich pyroclastic debris of the Early Black Flag Group; coarse polymictic volcanic debris of the Late Black Flag Group; thick piles of mafic lavas and sub-volcanic sills of the Athena Basalt and Condenser Dolerite; and the voluminous quartz-rich sedimentary successions of the Early Merougil Group. In the Argo-Junction region, these units have an interpreted maximum thickness of at least 7,130 m, and thus represent an unusually thick accumulation of the Neoarchean volcano-sedimentary successions. It is postulated that major basin-forming structures that were active during deposition and emplacement of the voluminous successions later acted as important conduits during mineralisation. Therefore, a correlation exists between the location of the largest gold deposits in the St Ives Goldfield and the thickest parts of the stratigraphy. Recognition of this association has important implications for camp-scale exploration.

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The mining industry presents us with a number of ideal applications for sensor based machine control because of the unstructured environment that exists within each mine. The aim of the research presented here is to increase the productivity of existing large compliant mining machines by retrofitting with enhanced sensing and control technology. The current research focusses on the automatic control of the swing motion cycle of a dragline and an automated roof bolting system. We have achieved: * closed-loop swing control of an one-tenth scale model dragline; * single degree of freedom closed-loop visual control of an electro-hydraulic manipulator in the lab developed from standard components.

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This paper reviews the state-of-the-art in the automation of underground truck haulage. Past attempts at automating LHDs and haul trucks are described and their particular strengths and weaknesses are listed. We argue that the simple auto-tramming systems currently being commercialised, that follow rail-type guides placed along the back, cannot match the performance, flexibility and reliability of systems based on modern mobile robotic principles. In addition, the lack of collision detection research in the underground environment is highlighted.

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Draglines are used extensively for overburden stripping in Australian open cut coal mines. This paper outlines the design of a computer control system to implement an automated swing cycle on a production dragline. Subsystems and sensors have been developed to satisfy the constraints imposed by the task, the harsh operating environment and the mines production requirements.

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This paper discusses some of the sensing technologies and control approaches available for guiding robot manipulators for a class of underground mining tasks including drilling jumbos, bolting arms, shotcreters or explosive chargers. Data acquired with such sensors, in the laboratory and underground, is presented.

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Purpose The purpose of this paper is to explore what the attitudes of small firm owner-managers are to developing the skills of their key resources and then examine how these and other factors affect owner-managers’ preferences for training these employees. Design/methodology/approach This study of training in small road transport firms in West Australia is cast in light of the literature on human resource management in small firms underpinned by insights drawn using the resource based view of the firm. Small firms (less than 20 people) dominate this industry, while the increasing freight task, and extreme distances between West Australian ports, towns and mines highlight this sectors’ importance. Survey results from 39 small road transport firms and interviews with nine owner-managers are analysed. Findings Legislative, regulatory and licensing requirements were shown to be a key determinant of skills development. Employers ensured that basic standards for employee certification and qualification were met, as the penalty for not doing so would be too high. Regulations drove the need for certain types of training – licenses, fatigue management, occupational health and safety, handling dangerous goods, the Maritime Security Identification Card card, forklift license, mine site inductions – while owner-managers knew where to get the training their staff needed. Although regulation appeared most visible in prescribing what happened in relation to training for drivers, the relevance of owner-managers’ attitudes could not be ignored, nor could conditions in the firms external environment as this shaped how these requirements were met. Research limitations/implications The RBV is useful in showing how skill development enabled similarity in skills across firms, while the attitudes owner-managers and economic and social conditions meant what happened in firms around skill development varied. The importance of small firm owner-managers’ attitudes are clearly highlighted and shown to influence organizational decisions and choices around training, but these were not independent of the regulatory framework and the economic and social conditions within which the firm operated. The small firms in this study did engage workers in formal training when necessary but it was put in the context of the idiosyncratic approach of the owner-manager and the day-to-day needs of the firm. “Training” was essentially about ensuring certain types of skills were held by employees and then passing on knowledge to ensure the behavior of employees was consistent with the owner-manager’s vision for the firm in its current environment. Originality/value Ways industry and government can encourage training activity that goes beyond the day-to-day firm needs are suggested.

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In the mining optimisation literature, most researchers focused on two strategic-level and tactical-level open-pit mine optimisation problems, which are respectively termed ultimate pit limit (UPIT) or constrained pit limit (CPIT). However, many researchers indicate that the substantial numbers of variables and constraints in real-world instances (e.g., with 50-1000 thousand blocks) make the CPIT’s mixed integer programming (MIP) model intractable for use. Thus, it becomes a considerable challenge to solve the large scale CPIT instances without relying on exact MIP optimiser as well as the complicated MIP relaxation/decomposition methods. To take this challenge, two new graph-based algorithms based on network flow graph and conjunctive graph theory are developed by taking advantage of problem properties. The performance of our proposed algorithms is validated by testing recent large scale benchmark UPIT and CPIT instances’ datasets of MineLib in 2013. In comparison to best known results from MineLib, it is shown that the proposed algorithms outperform other CPIT solution approaches existing in the literature. The proposed graph-based algorithms leads to a more competent mine scheduling optimisation expert system because the third-party MIP optimiser is no longer indispensable and random neighbourhood search is not necessary.

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Interaction of two different samples of graphene with DNA nucleobases and nucleosides is investigated by isothermal titration calorimetry. The relative interaction energies of the nucleobases decrease in the order guanine (G) > adenine (A) > cytosine (C) > thy mine (T) in aqueous solutions, although the positions of C and T seem to be interchangeable. The same trend is found with the nucleosides. Interaction energies of the A-T and G-C pairs are somewhere between those of the constituent bases. Theoretical calculations including van der Wools interaction and solvation energies give the trend G > A similar to T > C. The magnitudes of the interaction energies of the nucleobases with graphene are similar to those found with single-walled carbon nonotubes.