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By Hsin Wei Wu

A real-time Diesel Particulate Matter (DPM) monitor has been developed on the basis of the successful National Institute of Occupational Health and Safety (NIOSH) designed Personal Dust Monitor (PDM) unit. The objectives of a recently completed Australian Coal Association Research Program (ACARP) study were to modify the PDM to measure the submicrometre fraction of the aerosol in a real-time monitoring underground instrument. Mine testing focused on use of the monitor in engineering evaluations to determine how conditions can be improved. Studies, including a selection during Longwall (LW) moves as described in this paper, demonstrated how DPM concentrations from vehicles fluctuate under varying ventilation and operational conditions. Correlation between the current SKC DPM measurement system and real-time DPM monitors were conducted and results from six mines show a correlation between elemental carbon (EC) and the new monitor DPM mass ranging from .51 to .81 with R2 >.90. These differences are suspected to be due to variations from mine to mine in aspects such as mine atmospheric contamination, vehicle fleet variations, fuel type, engine maintenance, engine combustion efficiency, engine behaviour or interference from other submicrometre aerosol. Real-time monitoring readily reflects the movement of individual diesel vehicles and allows pin-pointing of high exposure zones such as those encountered where various vehicles work in areas of constrained or difficult ventilation. DPM monitoring approaches that have been available for some time based on shift average monitoring do not readily allow successful engineering evaluation exercises to determine acceptability of pollution levels. Identification of high DPM concentration zones allows efficient modification of mine ventilation, operator positioning and other work practices t o reduce miners? exposures without waiting for laboratory analysis results.

Jan 1, 2010

By Milan Yekich, Emanuele Cauda, Justin Patts, Cody Wolfe

This study presents the application of low-cost dust monitors (LCDMs) for real-time monitoring of respirable dust in a mining environment. LCDMs significantly enhance data collection by providing continuous, granular and cost-effective dust concentration readings. This case study demonstrates that by deploying LCDMs, mining operators can respond quickly to changes in dust levels, improving occupational safety and air quality management. The results show how such monitoring technologies can be integrated into routine operations to reduce dust exposure and prevent health hazards such as silicosis, especially when coupled with appropriate mitigation strategies.

Nov 1, 2024

By Milan Yekich, Emanuele Cauda, Justin Patts, Cody Wolfe

A worker’s personal exposure to respirable dust in occupational environments has traditionally been monitored using established methodologies which entail the collection of an 8-hour representative sample that is sent away for laboratory analysis. While these methods are very accurate, they only provide information on the average exposure during a specific time period, generally a worker’s shift. The availability of relatively inexpensive aerosol sensors can allow researchers and practitioners to generate real-time data with unprecedented spatial and temporal granularity. Low-cost dust monitors (LCDM) were developed and marketed for air pollution monitoring and are mostly being used to help communities understand their local and even hyper-local air quality. Most of these integrated sensing packages cost less than $300 per unit, in contrast to wearable or area dust monitors specifically built for mining applications which have been around for decades but still average around $5,000 each. At the National Institute for Occupational Safety and Health (NIOSH), we are leveraging the power of high-volume data collection from networks of LCDM to establish baseline respirable hazard levels and to monitor for changes on a seasonal basis as well as following any application of control technologies. We have seen the effective use and advantages of monitoring live data before, during, and after events like shift changes, operational changes, ventilation upgrades, adverse weather events, and machine maintenance. However, many factors have prevented a systematic adoption of LCDMs for exposure monitoring: concern for their analytical performance, the complexity of use, and lack of understanding of their value are some factors. This contribution outlines a one-year case study at a mine in Wisconsin USA, covering the installation, maintenance, data visualizations, and collaboration between NIOSH researchers and the industrial hygiene professionals at the mine.

Feb 1, 2024

By Kihong Park, Matthews C. Habjan, Arthur L. Miller

New Mining Safety and Health Administration (MSHA) regulations limit the mass concentration of airborne diesel particulate matter (DPM) or, more specifically, the concentration of elemental carbon (EC), in underground mines. The mine operators are responding by introducing a variety of controls to reduce DPM in the mines, potentially including the evaluation of new maintenance procedures to reduce underground mine vehicle emissions. There is currently a lack of an inexpensive and dependable method to directly measure the DPM concentration emitted from the vehicle tailpipe. To that end, this work demonstrated a simple field portable method for estimating the mass concentration of elemental carbon exiting the tailpipe of a diesel engine using a direct reading photometer. Simultaneous measurements of tailpipe exhaust were made with a Thermo Electron Personal DataRAM 1200 photometer (particulate mass concentration based on light scattering) and by analyzing PM2.5 and PM1.0 samples collected on quartz fiber filters using the National Institute of Occupational Safety and Health (NIOSH) method 5040 (mass concentration of EC via thermal-optical method). Results indicate surprisingly good correlation (R2 ) 0.97) of the two methods when the data are adjusted for relative humidity (RH) and corrected using an empirically generated calibration factor. Although preliminary, it may be possible to implement this method in maintenance shops to monitor emission trends and to compare emissions of various vehicles in a fleet. Such data will be useful for fleet planning to meet new air quality standards.

By J. A. Herbst

It is widely recognized that Semiautogenous Grinding (SAG) circuits require the use of effective process control techniques to achieve their full processing potential and to protect them from the harmful effects of overloads and grind-outs. This requirement is even more essential as the variability of the ore being processed increases. The new Chino Mines Company concentrator located near Santa Rita, New Mexico started operation in June of 1982. At least eight major rock types are mined and milled. Ore hardness, feed size, and specific gravity are quite variable. Typical feed rates per grinding line are 850-900 tph but extremes of 260-1200 tph have been encountered. Normal feed rate variations of between 400 and 1100 tph are encountered on a weekly and sometimes daily basis. Feed size varies with rock type from a maximum of eight inches for the harder ores to two inches for the softer ores. One somewhat unique characteristic of the Santa Rita ore body among major copper mines is the wide variation in ore specific gravity. Specific gravities of the major rock types range between 2.7 and 3.6. The specific gravity variations are due to large changes in magnetite concentration throughout the pit. The result of this is large variations in SAG mill throughput which can have a harmful effect on downstream ball milling and flotation performance. Due to these wide fluctuations in ore characteristics, it was recognized soon after startup that successful operation of the grinding circuit and the plant at large was dependent upon the development of an effective automatic grinding control strategy. Research at the University of Utah has suggested that control based upon critical but difficult or costly to measure variables would improve automatic control performance. A project team made up of the Chino process control staff, Kennecott's Process Control department and the University of Utah Metallurgy Department was established to assess these concepts at Chino. This paper describes the development and on-line plant implementation of an Extended Kalman Filter that uses simple models of the SAG milling process, to predict the volumetric loading, the rock mass, the water mass, and the ball mass within the SAG mills at Chino. The on-line estimation of these parameters is the first step in the development of an integrated SAG mill/ball mill control strategy which is hoped to L eventually maintain the grinding circuit at its maximum capacity, while balancing the grinding load between the SAG and ball mills. Examples of long term estimation with the models and filter are shown for typical operating conditions as well as a SAG mill overload and grind-out.

Jan 1, 1983

By R. Spring

Artificial intelligence, and especially expert systems, are currently receiving considerable attention. Of interest to the control engineer is the utilization of these tools for real-time process control applications. To evaluate this technology, a real-time expert control system was implemented in one of the grinding circuits at Brenda Mines Ltd. The performance of this micro computer based expert system compared satisfactorily to the proven supervisory control system currently in use. The study confirmed the expectations that expert systems have potential for real-time, supervisory control of mineral processing operations.

Jan 1, 1989

By J Moffatt, T Payten, N Spooner, L Teixeira, L A. Balzan, G Wilkie, G Tsiminis

Fluorine is a penalty element due to its reactive nature. In acidic environments many fluorine minerals dissolve to form hydrofluoric acid (HF), changing processing conditions. When smelted HF can be released, causing negative effects to nearby people and the environment, as well as potentially damaging the smelter. Sale of ore with high fluorine levels elicit a financial penalty or are banned outright. Real-time sensors create the opportunity for instantaneous decisions on ore processing due to changing conditions. A fluorine sensor would allow rises in fluorine concentration in a processing stream to be flagged, and decisions on processing conditions or diversion to stockpile before processing could be undertaken. As fluorine is a light element, it is difficult to detect with in-field XRF devices and does not work well with PGNAA. There are currently no existing sensors to quantify the presence of fluorine in real-time, and thus decisions based on fluorine grade cannot be made at minute- or even hour-scales. Sensors designed to measure the presence of minerals that contain fluorine are a possible avenue to enable the real-time detection of this element. Mineral-based sensing may also give an added advantage of additional information about how the fluorine will react under different processing steps. The authors were given a grant under CRC ORE II (project number P1–005) to search for mineralspecific signatures suitable for real-time analysis. The work focused on novel regimes and applications of fluorescence as a means to detect specific minerals. The aim was to exploit fluorescence responses unique to minerals of interest in mining systems in order to produce sensors that address gaps in existing capability. After the successful discovery of signatures specific to two major fluorine minerals an additional grant (P1–014) was funded to develop the research into a prototype on-belt sensor, in partnership with Scantech International Pty Ltd. This paper details the development of a sensor package through multiple Technology Readiness Levels (TRLs) through collaboration with government/industry grant schemes, academics from university, and a sensor-focused Mining Equipment and Technology Services (METS) company. We give a brief description of the new sensor technique and provide a case study of multi-disciplinary collaboration.

Aug 24, 2022

By A. F. van der Merwe, R-D. Taylor, M. Jacobs, F. H. Conradie

Total bound moisture (TBM) is a typical quality indicator of industrial-grade gypsum. This gypsum is comprised of three distinct phases, namely anhydrite, dihydrate, and hemihydrate, of which only the latter is of much industrial use. TBM analysis is a lengthy laboratory procedure, and an artificial neural network (ANN) TBM inference measurement is proposed as a fast and online alternative. An ANN inference model for gypsum TBM based on plant data was developed. The inputs to the network were primarily focused on the plant's calciner, and different network topologies, data divisions, and transfer functions were investigated. Furthermore, the applicability of the TBM value as a quality indicator was investigated based on a gypsum phase analysis. A strong correlation between TBM and the gypsum hemihydrate and anhydrite content was found, validating the plant target TBM of 5.8% as a quality indicator. A network topology consisting of one hidden layer with logarithmic-sigmoid (logsig) and pure linear (purelin) transfer functions showed the best performance (R > 90%).

Oct 3, 2023

By T Belligoi

Diamond cores and drill chips provide the only direct physical evidence for ore containing rocks. Early characterisation of cores and drill chips is important as it provides critical information for downstream processing. Traditional characterisation techniques include visual logging by a geologist or analytic and spectroscopic methods but they are time consuming and can miss some important textural or geomechanical features.The goal of this work is to evaluate the application of image analysis to iron ore cores and drill chips and to suggest improvements to existing core-scanning and chip monitoring systems. Two samples of massive ore differing by their mineralogy and texture, as well as two different batches of drill chips, have been imaged and analysed. Results are compared in function of the imaging system and the classification algorithms.As a conclusion, despite the necessity for more testing and improvements in calibration and lighting, it is obvious that image analysis technologies can bring a lot of useful information in the perspective of a geometallurgical mapping of the deposit.

Jul 11, 2011

An image analysis system has been built which automatically digitizes camera input of rock fragments, analyses the digitised data to determine the sizes and shapes of the rock fragments, and outputs the analysed data to a printer in the form of a histogram or a scatter chart. The high speed of such a system allows for direct collection of data from material thrown into the air by blasting, material travelling on a conveyor belt, and material free-falling on to a stock-pile or into or out of a rock-crusher. Data on the blasted, un-crushed material provides information on changes in the lithology and structure of the rock face as it is quarried or mined: flatter fragments may represent approach to a brittle, unstable shear zone, or a change from sandstone to shale; so that the informa- tion reflects the effect on the sizes and shapes of the fragments by the blasting process and/or by the rock structure. The size and shape distributions of rock fragments produced during blasting and during processing may now be continuously monitored. Such detailed analysis of the results of fragmentation is labour-intensive and expensive when the size and shape distributions are obtained manually, but is cheap and efficient when using this image analysis system. Such a system will enable the results of blasting, quarrying, mining and crushing to be cheaply analysed and correlated with current and changing indus- trial practice so leading the way to increased productivity.

Jan 1, 1988

By Hao Zhang

Site inspection is an important component of safety management system. In current practices, the inspectors evaluate the safety condition on a construction site with the assistance of a standardised checklist. However, the checklist emphasizes on evaluating the implementation of safety management system, but provides limited task-specific check items for assessing whether the individual construction tasks are conducted under safe condition and in a safe manner. To address this issue, the research presented in this paper aims to provide safety practitioners with comprehensive and taskspecific safety information to promote effective risk identification and facilitate strategic risk control during site inspection. Specifically, this research first builds a project-specific safety information database, which stores potential risks and control measures for each construction task. The research team then develops a mobile decision support tool to retrieve information from the database and support safer decision-making on site. The tool supports users in two ways: one is to provide daily risk checklists and risk control strategies to guide step-by-step inspection alongside the project schedule; the other is to let users input any safety-related keywords during the safety inspection process and the tool returns relevant safety information by applying text mining algorithms. It is ongoing research. This paper presents an overall research framework and discusses the progress in developing safety database and data retrieval concepts. The outcome of the project will help enhance safety management practices and reduce possible risky working conditions on a construction site.

Aug 1, 2013

Real-Time Integration of Mining and Metallurgical Information for Efficient Use of Energy and Water

Sep 13, 2010

By M. Buxton

"Advanced data acquisition and process modelling technology provides online data and decision support about different aspects of the resource extraction process. Real-time approaches have recently been applied to utilize the value of this information for improved production control in mineral resource extraction in different operational set ups including coal, polymetallic ore and gold deposits. The key concept of these approaches promotes the change in paradigm from discontinuous intermittent process monitoring to a continuous process and quality management system in the resource extraction process. The framework includes a real-time feedback control loop that rapidly links online material characteristics data acquired during extraction at the mining face, during material handling and processing with a sequentially up-datable resource model. This will allow near real-time optimization of decisions related to long-term planning, short-term sequencing and production control. The contribution reviews recent developments in the three main constituents sensor based material characterisation, rapid updating of grade control models and simulation based optimization for improved production control. Technological readiness is assessed and critical gaps for further technology development are identified. The value added is illustrated by means of selected case studies. INTRODUCTION With the depletion of known and established mineral reserves, the decrease in head grades and the continuing demand of mineral raw materials by the modern society, future exploitation will move towards extraction of deposits under geologically more complex conditions. Complex deposits are characterized by a low continuity in grade, presence of deleterious elements such as arsenic and high irregularity in the geometry of the ore boundaries. The profitable exploitation of such deposits becomes significantly more challenging. To be able to better utilize such unconventional mineral resources of the future, smart autonomous mining systems are needed, which integrate local exploration of spatially varying material characteristics in–situ and have the ability to follow and extract the pay zones in the ore body while minimizing dilution (Buxton and Benndorf, 2013). The main barriers to overcome for the successful economic exploitation are: • effective grade control which will maximize resource potential along the whole value chain, • minimization of handling zero-value material introduced by dilution, thus • reducing unnecessary expenditure of energy and financial resources and • management and control of the geological uncertainty due to limited information available,"

Jan 1, 2017

Falling asleep at the wheel of a moving vehicle is not only dangerous but avoidable. It is implicated in up to 30% of all road fatalities in general and up to 65% of mining incidents involving haulage trucks. These types of crashes normally result in serious injury and/or fatality due to the lack of breaking that occurs. However, when a 300 tonne haul truck has a sleep related crash it is not only the safety of the driver that has a high price but also the commercial impact on the mines? productivity and efficiency. We have been developing our ASTiD technology which stands for the Advisory System for Tired Drivers to seamlessly integrate in to Modular Mining?s Dispatch system to provide real-time early warning fatigue risk management. The benefits being driver shift optimisation, sustained productivity and of course less accidents. By monitoring the drivers alertness levels in real-time using ASTID, the Dispatcher becomes empowered to make critical, management decisions that will ultimately prevent serious injury or loss of life and the driver gets to stop when he needs to and not just when he is supposed to. This paper shows how this integrated solutions works.

May 1, 2011

By R. Lanthier, A. Broussaud, J. C. Guillaneau, D. Hodouin

This study presents a method for upgrading the information extracted from the measurements given by the sensors of a pilot grinding circuit. For that purpose raw signals are combined to process models for extracting, through filters, the best information on the process state. Two different filters are used; one is based on steady-state mass balance constraints and the other one uses dynamic mass balance equations allowing for material accumulation in the equipment. The filters are designed and tuned with the help of a grinding circuit dynamic simulator and are then implemented in the pilot plant. Their performances and usefulness are discussed.

Jan 1, 1989

By F. T. Cawood, M. N. M. Cudjoe

The ability to conduct real-time material tracking in mines has been a long-standing challenge. Technological innovations such as radio frequency identification technology (RFID) have over the years contributed to the effective tracking of material flow and reporting of metal content. This paper outlines the laboratory procedures and results from testing the suitability of microdot technology as a viable technique for real-time material tracking in mining. The paper clarifies the reasons for conducting the test and presents the material safety data sheet (MSDS) from a South African and Canadian perspective. Microdots from three aerosol systems were immersed in water, heated to 100°C, and crushed into coarse and fine material. These tests were used to ascertain if the technology could withstand mining conditions. A strength, weakness, opportunity, and threat (SWOT) analysis was used to evaluate and compare microdot technology with RFID. It was shown that microdot technology has some potential to track ore parcels because data integrity was retained after exposure to post-blast mining conditions. However, more improvement is required to digitally detect microdots before the technology can be implemented at scale in the mining industry.

Apr 2, 2022

By Kevin L. Gering

A detection method and apparatus have been developed to perform real-time measurement of aqueous free cyanide, C-. A laboratory prototype can measure cyanide ranging from 5 micrograms ,per liter to 100 milligrams per ?liter for analysis times as short as 2 minutes per measurement. Sample size per measurement is typically only a few mI, thus? minimizing the waste volume produced from spent samples. The basis for this detection device is a quantifiable, stable affinity between the electrode material and free cyanide in the sample; The electrode exhibits piezoelectric behavior, allowing it to be used as a microbalance. This technology 'has experienced two generations of laboratory prototypes, and has been thoroughly tested to determine the operational sensitivity toward process variables such as pH, competing reactions, etc. The speed and ,accuracy of this method make it superior to conventional wet chemistry methods used for quantifying cyanide levels in water. A device based on this technology could be useful in areas involving process monitoring and environmental compliance, .particularly in the cyanide-based leach mining industry. Interest for this detector has been shown by the gold mining industry and others. Patent application is in progress.

Jan 1, 1998

By W. P. Arnott

This paper presents real time photoacoustic measurements of diesel-soot black-carbon (BC or EC) and Dusttrak nephelometer total carbon (TC) concentrations in a Nevada gold mine. Comparisons with time-integrated filter-based measurements of EC and TC accomplished using the NIOSH 5040 method were found to be 50% smaller than the integrated real time measurements. This work was initiated primarily as a demonstration project for the usefulness of photoacoustic instruments in measuring BC in the mine environment. Real time black carbon measurements are very useful for determining miner exposure, for providing feedback in mine ventilation systems, and for quantifying machine specific emission rates to understand the operating conditions for specific machines that produce greatest black carbon concentrations. This paper reports real time measurements of DPM from a loaded and empty hauler as it is operated in a drift with a 12% grade. The photoacoustic instruments were demonstrated to be satisfactory for BC measurements in the mine environment.

Jan 1, 2009

By D Chalmers, C C. Harb

The detection and control of gas levels in mining is a continuing challenge for the industry. Standard detectors have many problems that could be overcome with laser based spectroscopic instruments, but to date these systems have not been suitable for mining conditions. This paper reports the development of a new digital data extraction scheme to modernise traditional cavity ring down spectroscopy (CRDS). CRDS is a direct cavity enhanced laser based absorption technique, which is used to allow the identification of an unknown substance by their molecular fingerprint; this unknown substance is identified by analysing the ring downtime of the light exiting the optical cavity. Traditional CRDS has many issues when analysing substances in hostile environments, or when multiple species may be present. This presents an alternative approach, called real-time CRDS (rtCRDS) that has the potential to overcome many of these issues and produces systems that could be used in the mining industry. The system utilises newly developed widely tuning quantum cascade lasers combined with improved optical cavities and novel digital data extraction to produce spectra over a 1500 nm range in a few seconds. The ring downtime measurements produced are accurate and have high sensitivity and maximum signal to noise ratio. This paper discusses the technique, illustrating the advantages compared to traditional systems and show real-time spectra for a set of molecules of interest to the mining industry. This paper also provided an analogy between this approach and that used in digital communications systems, and shows that this scheme is ideally suited to provide a network of sensors in hostile environments.CITATION:Harb, C C and Chalmers, D, 2015. Real-time methane detection – modern digital laser spectroscopy for hostile environments, in Proceedings The Australian Mine Ventilation Conference, pp 161–166 (The Australasian Institute of Mining and Metallurgy: Melbourne).

Aug 31, 2015

By N Jeannee, L Rattmann, M W. N Buxton, A deJong, K Nienhaus, A Soares, P Graham, A Korre, J Benndorf, D Buttgereit

The flow of information, and consequently the decision-making along the chain of mining from exploration to beneficiation, typically occurs in a discontinuous fashion over long timespans. In addition, due to the uncertain nature of the knowledge about deposits and the inherent spatial distribution of material characteristics, actual production performance often deviates from expectations. Reconciliation exercises to adjust mineral resource and reserve models and planning assumptions are performed with timely lags of weeks, months or even years.The key concept of real-time mining promotes a change in paradigm from discontinuous intermittent process monitoring to a continuous process and quality management system in the resource extraction process. The framework includes a real-time feedback control loop that rapidly links online data acquired during extraction at the mining face, material handling and processing with a sequentially updatable resource model. This will allow near real-time optimisation of decisions related to long-term planning, short-term sequencing and production control.The proposed framework integrates the following building blocks in a holistic manner: automated sensor-based material characterisationonline machine performance measurementsunderground navigation and positioningunderground mining system simulation and optimisation of planning decisionsupdating techniques for resource/reserve models.This paper introduces the real-time mining concept and the building blocks and provides a review of the state-of-the-art. Technological readiness of necessary building blocks is assessed, and critical gaps for further technology development are identified. The value added is illustrated by means of a case study.CITATION:Benndorf, J, Buxton, M W N, Nienhaus, K, Rattmann, L, Korre, A, Soares, A, deJong, A, Jeannee, N, Graham, P, Buttgereit, D, Gehlen, S, Eijkelkamp, F, Mischo, H, Sandtke, M and Wilsnack, T, 2015. Real-time mining – moving towards continuous process management in mineral resource extraction, in Proceedings Third International Future Mining Conference, pp 37–46 (The Australasian Institute of Mining and Metallurgy: Melbourne).

Nov 4, 2015