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By Zephaniah Varley, Satoshi Akai, Richard Sage, Steve Redmond, Mike Murray, Rohit Shetty, Gerald Skalla

One would be hard pressed to find another project as complex as this one given its configuration, the variety of issues to address and the required construction techniques. Contract C710 is currently under construction as part of Sound Transit’s Link Light Rail, connecting downtown Seattle with Sea-Tac Airport. The paper describes the construction-to-date of the deep mined station under Beacon Hill using the Sequential Excavation Method (SEM). This deep “binocular” station is being mined through some of the most challenging soft ground conditions in the USA. The excavated volume of the station is approximately 60,000 cy (46,000 m3) and the station comprises a variety of geometries and cross sections ranging from 235 sf (22 m2) up to 1,670 sf (155 m2). This underground complex includes platform, concourse, cross-passage and emergency ventilation tunnels together with station egress and ventilation shafts. Various excavation sequences are in use for the different tunnels including the twin-sidewall drifts for the impressive45 ft (13.7 m) wide by 42 ft ( 12.8 m) high concourse cross adits. This station has two train platforms approximately 165 feet (50m) below the surface. This station, constructed in highly variable glacial deposits including water bearing sands and silts approximately 50 ft below multiple perched water tables in an urban setting, creates a very unique and challenging situation. The ground is being managed with various types of ground improvements such as jet grouting and vacuum assisted deep dewatering wells from the surface, and from underground by use of “SEM Tool-box Items” such as barrel vault canopy, grouted pipe and rebar spiling, chemical grout,

Jan 1, 2007

By Shimi Tzobery, John E. Shamma, Samuel Swartz, Gary B. Hemphill

The trapezoidal tapered ring method has made significant progress in recent years for shielded-TBM projects, excavating tunnels with high overburden, strict water tightness criteria, and multiple curve alignments. The selection of compatible tapered rings is critical for successful advancement of the tunnel, assuring efficient installation of rings, as well as prevention of ring damage and excessive leakage. Using experience from the Arrowhead Tunnels Project, this paper describes guidelines for ring selection in tunnel curves, geometric analyses that comply with criteria principals, and provides techniques developed to determine the appropriate relative key position.

Jan 1, 2005

By A. L. Martikainen

In fluctuating airflow, continuous air velocity recording is the most reliable method of air velocity measurement. It allows for fast recognition of changes and the calculation of long-term averages. Also, it enables the mine operator to identify when the airflow has decreased to a point requiring action. Using ultrasonic anemometers provides an accurate option for continuous air velocity monitoring. This paper provides information about the effect of common obstructions in underground mining on air velocity readings. Stationary and moving obstructions are used to represent workers and equipment that would cause discrepancies in measured airflow. Also, it is important to know how large of a sample size is required to ensure reasonable accuracy of results. Statistical analysis is used to evaluate the required sample size. The sampling procedure is further studied by comparing two different sample rates. The results show that obstructions provide noticeable differences in air velocity measurements. Also, movement of obstructions can be recognized from changes in results. Surprisingly small sample sizes provide reliable air velocity information. Standard sample rates are found to be suitable for the underground environment.

Jan 1, 2011

The management of risks associated with slope instability is an essential process in the safe and economic operation of open cut mines. The ?slope stability radar? (SSR) has been developed to better manage those risks. The SSR remotely scans rock slopes to continuously measure any surface movement and can be used to detect and alert users of wall movements with sub-millimeter precision. The high level of movement precision and broad area coverage of the rock face can allow for a better understanding of the geomechanics of slope deformation, including magnitude of potential failures and additional warning time of impending instability. Additionally, radar waves adequately penetrate through rain, dust and smoke to give reliable measurements, 24 hours a day. SSR systems have been deployed in many metalliferous and coal mines throughout the world. Over 80 systems are currently being used with current operations in 17 countries. Greater than 200 rock slope collapses and waste dump failures (from several to millions of tones) have been monitored, with ?warning? precursor movements recorded by the SSR. This technology enables a radical change in the management of risks in open cut mining. This paper will present recent case studies of the SSR operation in coal and metalliferous mines. Slope Stability Hazards and Rock Slope Monitoring in Open Pit Mines Surface mining often creates excavation boundaries which are steeper than those would be created under natural processes in the same rock type. They are also undertake quite rapid stress changes during mining and are influenced by significant external forces such as blast vibrations and changes in groundwater. These conditions are likely to allow some degree of instability to develop in the pit slopes. The hazards associated with this instability of pit slopes can be extremely variable in character; ranging from small cobble sized rocks dislodging and falling from mine benches to complete collapse of entire pit walls. It is usually the position of mine geotechnical or geological staff to assess these hazards for mine operations. The assessment of hazards due to unstable slopes can be done by visual observation of precursor signs such as fracturing or rilling of loose material. A more reliable indicator of instability involves the quantitative measurement of outward movement and acceleration of material as an instability mechanism develops. There is strong evidence that small precursor movements of a rock wall occur for an extended period prior to rock slope collapse (Hoek and Bray, 1981). Development of a monitoring system, adopting acceptable slope deformation criteria coupled with warning systems and design of stabilization or risk reduction measures if appropriate has become a standard method of dealing with slope instability. Framework for Slope Hazard Management using the SSR A framework for the management of slope hazards is shown in Figure 1 (discussed in detail in Harries, 2007). Although this framework is specifically for use with the Slope Stability Radar, a similar framework could be developed for other monitoring technologies for monitoring slope deformation. An important point to consider is the sequential nature of the hazard management framework from selecting the context ? identifying hazards ? analysing hazards ? evaluating hazards ? treating hazards. [ ] Once the context of the system has been developed (for example ? to monitor for rapid bench scale collapse), the identification of hazards is the next stage in hazard management. Identification of slope hazards can be relatively straightforward due to the visual nature of the information that the SSR system produces. The areas of excessive wall deformation are highlighted in color maps of the mine slope with a co-aligned photographic image to review the actual site of interest. The responsible personnel must then analyses this data, usually reviewing the deformation style and rate, as well as the size of area that appears to be failing. This information can then be evaluated against organisation protocols (for example it may be only a small sub-bench failure that will be ?caught? by existing benches and hence can be categorized as a lower risk). Once these hazards are evaluated they can then be treated if required. Two major options are available to reduce the risk during this treatment option. We can reduce the likelihood of failure ? for example by buttressing the failure or de-pressurising of water pressures in a slope. However, the most likely plan of action is to reduce the consequence of the failure. One of the most successful opportunities to reduce the consequence of a slope failure is to ensure that no personnel or mining equipment is present at the location of a slope failure when collapse finally occurs. This has been the major benefit of the SSR system to the different mining operations around the world. SLOPE STABILITY RADAR TECHNOLOGY OUTLINE Slope Stability Radar system specifications and capabilities: ? Measurement precision +/- 0.1mm (std.) ? Perforated dish and other features enable it to operate in high wind conditions ? Measurement range is 1700 metres ? Scans 270 degrees horizontally and 120 degrees vertically ? 1 ? 30 minute repeat rate for area scans (varies according to area being scanned ? RF exposure (<0.05mW/cm2) is a factor of 200 below the acceptable limit for the general population (1 mW/cm2) ? Tolerant to vibration and mining equipment ? The system weighs approximately 1500 Kg ? Remote area power supply enabling unmanned, continuous 24/7 monitoring ? Real time monitoring

Jan 1, 2009

By P. C. Thakur

Frictional ignitions (also called face ignitions) is defined as the rapid oxidation of a mixture of methane and air with a visible flame that could last from a few seconds to several minutes. These ignitions have a potential to turn into a mine explosion and eventually a large-scale mine fire. Over the last 22 years, U.S. coalmines have had 1566 frictional ignitions. There were no fatalities but serious injuries have occurred. Every effort, therefore, should be made to prevent frictional ignitions. The preventative measures fall under four categories: (a) degasification of coal seams prior to mining, (b) adequate ventilation, (c) wet cutting or water-jet assisted cutting and (d) machine design to minimize ignitions. The paper discusses each of these techniques in detail.

Jan 1, 2006

By Rambabu Pothina, Rajive Ganguli

The economics of a mineral processing circuit is dependent on the numerous sensors that are critical to optimization and control systems. The sheer volume of sensors results in mines not being able to keep the sensors calibrated. When a sensor goes off calibration, it results in errors which can severely impact plant economics. Normally, these errors are not detected until the error grows and becomes a large (“gross”) error. Undetected errors are not remedied until the next calibration, which on average are a year apart Beamex (2019) [1] across all industries. Classical statistical methods that depend on linear relationships between input and response variables are typically used to find gross errors, but are not effective for highly non-linear and non-stationary operations in mining and mineral processing industries. Calibration of sensors is time-consuming and generally requires physical intervention that results in equipment downtimes causing production losses. Therefore, in situ detection methods are warranted that do not require physical removal of sensors to compare with standard measurements or well-calibrated sensors. Data-mining based techniques and algorithms have high success rate in tackling such problems. This paper presents results from a groundbreaking multi-year big data research project whose goal was to develop data-mining-based original techniques in a multi-sensor environment to identify when sensors start to stray, rather than wait for errors to grow. The carbon stripping (gold) circuit in the Pogo Mine of Alaska was selected for this project. Maintaining strip vessel temperatures at optimum levels is crucial for maximizing gold recoveries at Pogo, and hence the focus was on the temperature sensors of the two strip vessels. An automated algorithm to detect errors in strip vessel temperature sensors was developed that exploited data from multiple sensors in the strip circuit. This algorithm was able to detect with a high success rate when bias errors of magnitude as low as ± 2% were artificially induced into strip vessel temperature data streams. The detection times of about 1 month were much less than the industry average calibration frequency of 1 year. Thus, the algorithm helps detect errors early, without stopping the circuit. The algorithm alarms can serve as triggers when calibrations are done. Experimental methodology along with results, limitations of algorithms, and future research are also presented in this paper.

By Rambabu Pothina, Rajive Ganguli

The economics of a mineral processing circuit is dependent on the numerous sensors that are critical to optimization and control systems. The sheer volume of sensors results in mines not being able to keep the sensors calibrated. When a sensor goes off calibration, it results in errors which can severely impact plant economics. Normally, these errors are not detected until the error grows and becomes a large (“gross”) error. Undetected errors are not remedied until the next calibration, which on average are a year apart Beamex (2019) [1] across all industries. Classical statistical methods that depend on linear relationships between input and response variables are typically used to find gross errors, but are not effective for highly non-linear and non-stationary operations in mining and mineral processing industries. Calibration of sensors is time-consuming and generally requires physical intervention that results in equipment downtimes causing production losses. Therefore, in situ detection methods are warranted that do not require physical removal of sensors to compare with standard measurements or well-calibrated sensors. Data-mining based techniques and algorithms have high success rate in tackling such problems. This paper presents results from a groundbreaking multi-year big data research project whose goal was to develop data-mining-based original techniques in a multi-sensor environment to identify when sensors start to stray, rather than wait for errors to grow. The carbon stripping (gold) circuit in the Pogo Mine of Alaska was selected for this project. Maintaining strip vessel temperatures at optimum levels is crucial for maximizing gold recoveries at Pogo, and hence the focus was on the temperature sensors of the two strip vessels. An automated algorithm to detect errors in strip vessel temperature sensors was developed that exploited data from multiple sensors in the strip circuit. This algorithm was able to detect with a high success rate when bias errors of magnitude as low as ± 2% were artificially induced into strip vessel temperature data streams. The detection times of about 1 month were much less than the industry average calibration frequency of 1 year. Thus, the algorithm helps detect errors early, without stopping the circuit. The algorithm alarms can serve as triggers when calibrations are done. Experimental methodology along with results, limitations of algorithms, and future research are also presented in this paper.

By W. F. Visser

The growing availability of information and data analysis capabilities of recent years provides new opportunities for improving the performance of mining operations. By using real-time measurements and artificial intelligence, it is possible to respond faster to changing conditions, while accurate and timely information permits rapid evaluation of changes and fast business improvement decisions. This article presents a blueprint for alignment of systems, organizational design, and management practices to leverage these developments in performance-driven operations management in mining and mineral processing. The first component of the blueprint is a performance framework with a system of key performance indicators for production control that can be used across organizational levels. This system places improvement at the core of management activities, giving greater importance to improvement skills at lower organizational levels, so companies can leverage available information for improving operational control. Secondly, the blueprint defines an organizational structure that strengthens performance improvement with technological and change management capabilities. Finally, the blueprint proposes alignment of management practices, covering the optimization of short-interval controls, the application of an improvement project portfolio management system that determines the ownership of improvement projects, and the coordination of controls across the organization. This combination of systems, organizational design, and management alignment supports rapid decision-making at the right organizational level. Introduction of the presented blueprint for operations management enables mines to leverage the developments in information and analysis capabilities to improve the performance of operations.

By Paul F. Ziemkiewicz, Aaron Noble, Christopher R. Vass

The conventional rare earth element (REE) industry has historically sought to develop ore deposits where geologic processes have produced mineralized zones with commercially attractive REE concentrations. These deposits are extremely uncommon, particularly in the USA. Given the criticality of these materials and the need for sustainable domestic supply, the current research seeks to leverage other autogenous processes that lead to concentrated REE resources. One such process is the generation of acid mine drainage (AMD). AMD is very common in many coal mining districts and results from the exposure and oxidation of pyrite during mining. During the generation and migration of AMD, liberated sulfuric acid mobilizes several metal ions including REEs. Treatment of AMD is required under U.S.C §1251, the Clean Water Act, and often consists of neutralization, oxidation, and metal hydroxide precipitation. To investigate the deportment of REEs during this process, a field sampling campaign was undertaken, whereby the concentration of REEs in AMD and AMD precipitates was measured directly. In the nine sites evaluated in this study, the REE concentrations of the precipitates varied from 29 to 1286 ppm with an average of 517 ppm among the sampled sites. The individual elements were enriched compared with the associated bulk Northern Appalachian (NAPP) coal material by factors ranging from 3 to 15. Furthermore, the distribution of REEs in all precipitate samples favored the heavy REEs (HREEs) when compared with traditional REE ores. This research represents the first part of multi-part research endeavor to characterize, classify, and determine the practicality of refining REEs from AMD and its by-products.

By Paul F. Ziemkiewicz, Aaron Noble, Christopher R. Vass

The conventional rare earth element (REE) industry has historically sought to develop ore deposits where geologic processes have produced mineralized zones with commercially attractive REE concentrations. These deposits are extremely uncommon, particularly in the USA. Given the criticality of these materials and the need for sustainable domestic supply, the current research seeks to leverage other autogenous processes that lead to concentrated REE resources. One such process is the generation of acid mine drainage (AMD). AMD is very common in many coal mining districts and results from the exposure and oxidation of pyrite during mining. During the generation and migration of AMD, liberated sulfuric acid mobilizes several metal ions including REEs. Treatment of AMD is required under U.S.C §1251, the Clean Water Act, and often consists of neutralization, oxidation, and metal hydroxide precipitation. To investigate the deportment of REEs during this process, a field sampling campaign was undertaken, whereby the concentration of REEs in AMD and AMD precipitates was measured directly. In the nine sites evaluated in this study, the REE concentrations of the precipitates varied from 29 to 1286 ppm with an average of 517 ppm among the sampled sites. The individual elements were enriched compared with the associated bulk Northern Appalachian (NAPP) coal material by factors ranging from 3 to 15. Furthermore, the distribution of REEs in all precipitate samples favored the heavy REEs (HREEs) when compared with traditional REE ores. This research represents the first part of multi-part research endeavor to characterize, classify, and determine the practicality of refining REEs from AMD and its by-products.

By D. N. Adams, M. M. Wong, M. J. Robison

Islais Creek Contract E, a transport/storage tunnel in San Francisco, was visited on a fieldtrip during construction by delegates to the 1995 RETC. This paper is a follow-up to that fieldtrip. The project’s two tunnels are 3.7 m and 3.2 m finished diameter, 155 m and 77 m long, respectively. The contractor used 1,000 overlapping jet grout columns to pre-treat the weak Bay Mud along the tunnel alignments, then mined them with an open faced tunnel shield, eliminating the need for compressed air tunneling. This paper documents the jet grouting program and the tunneling operation used on the project.

Jan 1, 1997

By J. B. Platt

Many utility fuel choices 1990-95 defied expectations, with utility decisions and coal market developments ever more closely linked. The Central Appalachian coal boom never occurred; clean-enough coal was developed in the hard-hit Midwest; Colorado-Utah coal surged; Pittsburgh seam production strengthened; utilities embraced Powder River Basin coal; and emission allowance prices collapsed. Competition drove productivity gains, but the future is not a simple repeat. Phase 2 brings fewer viable compliance options. Mega-railroad pricing has become a key risk factor -- will this be countermanded by merging utilities and power market competition? Revenue losses from vintage contracts are problematic. Uncertainty also plagues natural gas, in spite of unanimity across major forecasts, since recent experience has been so heavily influenced by the gas bubble.

Feb 24, 1997

By Yi Luo, Jian Yang, Hua Jiang

Surface subsidence events induced by underground longwall coal mining operations can cause various disturbances to surface structures ranging from integrity and stability to functionality problems. Highway bridges, as a kind of special road construction that can only tolerate smaller movements and deformations than road pavements, are particularly susceptible to severe influence caused by subsidence-induced ground movements and deformations. However, based on accurate subsidence prediction and correct influence assessments, efficient and effective mitigation and remediation measures can be designed and implemented to ensure the continuous service of bridges, safety of the travelers and smooth mining operations. In this paper, based on the predicted final and dynamic surface movements and deformations, the techniques to assess subsidence influence on the integrity, stability and functionality of bridge structures (e.g., decks, beams, abutments, etc.) are presented. A number of mitigation measures to protect the bridge structures are recommended along with an actual application case.

By John Marsden, Mike Botz

A variety of modeling techniques can be utilized to forecast metal production at heap leaching operations. These approaches reflect a wide range of complexity, flexibility, time to implement, cost, and accuracy. For many operators, a spreadsheet-based modeling technique is attractive since the calculations are directly accessible, models can often be developed by site staff, and the results are generally easy to extract and interpret. The authors have developed a spreadsheet-based modeling technique that provides a high degree of flexibility, while still considering detailed operating information for ore properties, leach kinetics, scaleup factors, lift height, and in-heap metal inventories. The technique involves establishing kinetic leach curves for each ore type to characterize metal extractions, followed by application of separate metal recovery curves to define the rate at which leached metals exit the heap in pregnant solution, taking into account delays due to the in-heap solution inventory. At any point in time, the difference between total metal extracted and total metal recovered is equal to the in-heap inventory of the leached metal. This modeling technique is particularly useful for larger multi-lift heaps where delays in metal recovery are appreciable due to in-heap solution holdup. The technique is also applicable to sites with multiple heaps, leach cycles, and/or metal recovery plants (e.g., carbon columns for gold; solvent extraction for copper). This paper describes the modeling technique, including input data required and methods for defining kinetic leach curves and metal recovery curves. The technique is compared against an alternative spreadsheet technique using a simplified in-heap solution inventory calculation to forecast metal production, which has proven to be effective at a number of sites.

By John Marsden, Mike Botz

A variety of modeling techniques can be utilized to forecast metal production at heap leaching operations. These approaches reflect a wide range of complexity, flexibility, time to implement, cost, and accuracy. For many operators, a spreadsheet-based modeling technique is attractive since the calculations are directly accessible, models can often be developed by site staff, and the results are generally easy to extract and interpret. The authors have developed a spreadsheet-based modeling technique that provides a high degree of flexibility, while still considering detailed operating information for ore properties, leach kinetics, scaleup factors, lift height, and in-heap metal inventories. The technique involves establishing kinetic leach curves for each ore type to characterize metal extractions, followed by application of separate metal recovery curves to define the rate at which leached metals exit the heap in pregnant solution, taking into account delays due to the in-heap solution inventory. At any point in time, the difference between total metal extracted and total metal recovered is equal to the in-heap inventory of the leached metal. This modeling technique is particularly useful for larger multi-lift heaps where delays in metal recovery are appreciable due to in-heap solution holdup. The technique is also applicable to sites with multiple heaps, leach cycles, and/or metal recovery plants (e.g., carbon columns for gold; solvent extraction for copper). This paper describes the modeling technique, including input data required and methods for defining kinetic leach curves and metal recovery curves. The technique is compared against an alternative spreadsheet technique using a simplified in-heap solution inventory calculation to forecast metal production, which has proven to be effective at a number of sites.

By John Marsden, Mike Botz

A variety of modeling techniques can be utilized to forecast metal production at heap leaching operations. These approaches reflect a wide range of complexity, flexibility, time to implement, cost, and accuracy. For many operators, a spreadsheet-based modeling technique is attractive since the calculations are directly accessible, models can often be developed by site staff, and the results are generally easy to extract and interpret. The authors have developed a spreadsheet-based modeling technique that provides a high degree of flexibility, while still considering detailed operating information for ore properties, leach kinetics, scaleup factors, lift height, and in-heap metal inventories. The technique involves establishing kinetic leach curves for each ore type to characterize metal extractions, followed by application of separate metal recovery curves to define the rate at which leached metals exit the heap in pregnant solution, taking into account delays due to the in-heap solution inventory. At any point in time, the difference between total metal extracted and total metal recovered is equal to the in-heap inventory of the leached metal. This modeling technique is particularly useful for larger multi-lift heaps where delays in metal recovery are appreciable due to in-heap solution holdup. The technique is also applicable to sites with multiple heaps, leach cycles, and/or metal recovery plants (e.g., carbon columns for gold; solvent extraction for copper). This paper describes the modeling technique, including input data required and methods for defining kinetic leach curves and metal recovery curves. The technique is compared against an alternative spreadsheet technique using a simplified in-heap solution inventory calculation to forecast metal production, which has proven to be effective at a number of sites.

Sep 3, 2019

By Antti Porvali, Vivek Agarwal, Mari Lundström

Hydrometallurgical recovery of rare earth elements (REE) from NiMH battery waste can be performed using sulfuric acid leaching followed by selective precipitation as double salt (REENa(SO4)2·H2O) by adding Na2SO4 as a precipitating agent. The formed double salts can then be further converted with NaOH solution to form REE hydroxides. However, present literature has paid little attention to how to minimize the consumption of reagents in this recovery process. In the current study, a process model was built using HSC Sim software, and metamodeling of the simulated flowsheet was conducted with the design of experiments (DOE), after which the basic functionality of the flowsheet was verified by experimental work, starting from sulfuric acid leaching of spent batteries. As the process is based on chemical circulation internally in the process, the objective was to investigate the accumulation of the elements in solution, specifically Na+ , K+ , SO4 2− ions and impurities liberated in the NaOH conversion step. It was found out that metamodeling could be utilized in obtaining first estimate of the process behavior, prior to any experiments. Flowsheet functionality with circulated solution was confirmed, obtaining at best 96.9% La recovery.

By Antti Porvali, Vivek Agarwal, Mari Lundström

Hydrometallurgical recovery of rare earth elements (REE) from NiMH battery waste can be performed using sulfuric acid leaching followed by selective precipitation as double salt (REENa(SO4)2·H2O) by adding Na2SO4 as a precipitating agent. The formed double salts can then be further converted with NaOH solution to form REE hydroxides. However, present literature has paid little attention to how to minimize the consumption of reagents in this recovery process. In the current study, a process model was built using HSC Sim software, and metamodeling of the simulated flowsheet was conducted with the design of experiments (DOE), after which the basic functionality of the flowsheet was verified by experimental work, starting from sulfuric acid leaching of spent batteries. As the process is based on chemical circulation internally in the process, the objective was to investigate the accumulation of the elements in solution, specifically Na+ , K+ , SO4 2− ions and impurities liberated in the NaOH conversion step. It was found out that metamodeling could be utilized in obtaining first estimate of the process behavior, prior to any experiments. Flowsheet functionality with circulated solution was confirmed, obtaining at best 96.9% La recovery.

By Yves St-Amour, Vince Luongo

This paper will discuss one of the largest construction projects the City of Portland has undertaken. This phase of the Willamette River Combined Sewer Overflow (CSO)project consists of approximately 18,500 ft of tunnel in soft ground, requiring the construction of six deep shafts and jet grout ground improvement. The purpose of the project is to reduce volume of combined sewerage overflows from the drainage areas on the west side of the Willamette River. Bencor-Petrifond-Pacchiosi Joint Venture was awarded a contract to design and construct six deep circular shafts, jet grout ground improvement for three bridges and jet grout ground improvement break-in/outs for some shafts. Of the six shafts the Pumping Station Shaft was the deepest and largest, requiring a permanent ground support system with a deep jet grout ground water cut-off to 335-ft deep. The joint venture used state of the art methods and equipment to achieve its objectives and build the structures through some very difficult alluvial soils to great depths next to the Willamette River. The paper will provide a general discussion of the shaft construction and jet grout ground improvement installed for this phase of the project. It will also discuss some of the technical challenges encountered while effectively managing risk and costs, resulting in a successful project completed in a timely manner.

Jan 1, 2005

By Jacob Carr, Christopher C. Jobes, Chenming Zhou, LaTasha R. Swanson, Jennica Bellanca, Jingcheng Li

Magnetic proximity detection systems (PDSs) are used with continuous mining machines (CMMs) to protect miners from striking and pinning accidents. Generators are used in a PDS to create magnetic fields covering the space around a CMM. The PDS determines the proximity of a miner relative to the CMM based on the magnetic flux density detected by a miner-wearable component (MWC) and simultaneously alerts the miner and stops the motion of the CMM if the miner is within a proximity that creates a striking hazard. A stable magnetic field is essential to the accuracy of the proximity calculations performed by the PDS. This paper presents the results of a systematic study of the magnetic influence of two types of steel structures found near a CMM— the body of the CMM itself and the wire mesh used for roof and rib control. The results show that the steel of the CMM body can change the magnetic field distribution and also alter electrical parameters of a PDS by changing its generator current. The study also shows that, depending on the distance between the wire mesh and a generator, the magnetic field can also be altered.