Review of radar system performance and estimation of slope deformation threshold values for the Leveäniemi open pit

Slope stability is crucial for safety in operations during open pit mining. A slope failure could influence the environment, lead to human injuries and economic losses. To ensure proper management and mitigation of the stability problems it is necessary to provide accurate slope designs and constant and accurate slope monitoring procedures. There are many techniques that are used for the slope monitoring. One of the most effective methods is the slope stability radar (SSR) technology. It allows for 24 h per day, real-time monitoring of slopes in all-weather condition. The SSR covers a large expanse of the wall slope and can detect deformations within the slopes well before slope failure occurs. This makes the SSR as an effective tool for an early warning signal for an impending slope failure. One of the requirements is the availability of the line of sight between the SSR and the monitored wall. This study aims at reviewing the threshold values for input into a slope stability radar which is being installed at the one of Svappavaara open pit’s- Leveäniemi open pit, for monitoring slope stability. The Leveäniemi open pit is located near Svappavaara in Swedish Lapland and is a part of LKAB. Threshold values are difficult to set as they depend on so many rock mass properties and pit geometry, which in turn also change from place to place (site-specific). Around the world, many mines use radar systems for the protection of slopes and avoidance of slope failure. Therefore, the threshold value for the Leveäniemi open pit will be estimated using other case studies. An expected outcome of the research is a range of deformation at which the SSR will give an early warning signal against a likely failure in the pit slopes. Moreover, the study will determine operating procedures for the radar system to be installed and establish a smooth reporting system for the data gathered through the radar

Multi-function intelligent robotic in metals detection applications

Recent technologies for robotics have been offered an effective and efficient solution to safeguard workers from risks in their work environments. These risks involve radioactive, toxic, explosive and mines. In this paper, design and implement computer robot based on metal detection as well as avoiding obstacles automatically. The proposed wireless controlled robotic vehicle can be used in metal detection applications such as landmine detection, obstacles avoidance, selecting best routing without imposing human's harms and workforce aspects. The robotic wheel can sense the obstacles that positioning at ahead of its path, and also avoids the obstacles forward, left and right of its routes. The robot is controlled by using Bluetooth wireless communication to interface between the controller and the implemented robot. Furthermore, sensor IR (FC-03) for the metal detector and used ultrasonic sensor (HC-SR04) for objects or obstacles sensing. The presented controlled robotic designed for desert and dry soil that can replace the human role in avoiding obstacles and metal detection capabilities. The produced robot was useful due to it can detect metals and avoiding obstacles consecutively besides it was effective to select the best route based on the intelligent technique that adopted, the predefined metals by using an intelligent decision maker for route finder in a flat surface environment

Project OASIS: The Design of a Signal Detector for the Search for Extraterrestrial Intelligence

An 8 million channel spectrum analyzer (MCSA) was designed the meet to meet the needs of a SETI program. The MCSA puts out a very large data base at very high rates. The development of a device which follows the MCSA, is presented

Analysis and Design of a secure WLAN solution for Cobre Las Cruces

Cobre Las Cruces is a renowned copper mining company located in Sevilla, with unexpected problems in wireless communications that have a direct affectation in production. Therefore, the main goals are to improve the WiFi infrastructure, to secure it and to detect and prevent from attacks and from the installation of rogue (and non-authorized) APs. All of that integrated with the current ICT infrastructure. This project has been divided into four phases, although only two of them have been included into the TFC; they are the analysis of the current situation and the design of a WLAN solution. Once the analysis part was finished, some weaknesses were detected. Subjects such as lack of connectivity and control, ignorance about installed WiFi devices and their localization and state and, by and large, the use of weak security mechanisms were some of the problems found. Additionally, due to the fact that the working area became larger and new WiFi infrastructures were added, the first phase took more time than expected. As a result of the detailed analysis, some goals were defined to solve and it was designed a centralized approach able to cope with them. A solution based on 802.11i and 802.1x protocols, digital certificates, a probe system running as IDS/IPS and ligthweight APs in conjunction with a Wireless LAN Controller are the main features

DECISIONS IN THE DARK: A FRAMEWORK FOR DECISION-MAKING IN UNFAMILIAR SITUATIONS

This thesis seeks to understand an appropriate decision-making framework for the fire service to use in unfamiliar situations. Firefighters and emergency responders rely on pattern recognition when they are presented with familiar situations; however, relying on such intuition can result in costly time delays. A case study method was used to evaluate decision-making during disasters in the fire service and the mining industry. The fire service cases include the 1949 Mann Gulch Fire and the fire service response to the 9/11 attack on the World Trade Center. The mining case studies, both of which occurred in 2010, include the Deepwater Horizon oil spill and the Chilean mine collapse. The fire service cases were assessed to determine which decision-making tools were utilized and what additional factors influenced positive and negative outcomes throughout the events. The mining cases were evaluated to understand organizational structures and response systems. This thesis recommends that fire service leaders utilize expanded interdisciplinary teams to creatively seek alternative solutions when addressing unfamiliar problems. Using such teams will require leaders to expand response frameworks and alter familiar patterns of response to include outside agencies and nontraditional emergency responders. Finally, leaders should deliberately encourage open communication about successes and failures to encourage collaboration and innovation throughout the response.Civilian, Portland Fire and RescueApproved for public release. Distribution is unlimited

Advances in Computational Intelligence Applications in the Mining Industry

This book captures advancements in the applications of computational intelligence (artificial intelligence, machine learning, etc.) to problems in the mineral and mining industries. The papers present the state of the art in four broad categories: mine operations, mine planning, mine safety, and advances in the sciences, primarily in image processing applications. Authors in the book include both researchers and industry practitioners

3D SEM Surface Reconstruction: An Optimized, Adaptive, and Intelligent Approach

Structural analysis of microscopic objects is a longstanding topic in several scientific disciplines, including biological, mechanical, and material sciences. The scanning electron microscope (SEM), as a promising imaging equipment has been around to determine the surface properties (e.g., compositions or geometries) of specimens by achieving increased magnification, contrast, and resolution greater than one nanometer. Whereas SEM micrographs still remain two-dimensional (2D), many research and educational questions truly require knowledge and information about their three-dimensional (3D) surface structures. Having 3D surfaces from SEM images would provide true anatomic shapes of micro samples which would allow for quantitative measurements and informative visualization of the systems being investigated. In this research project, we novel design and develop an optimized, adaptive, and intelligent multi-view approach named 3DSEM++ for 3D surface reconstruction of SEM images, making a 3D SEM dataset publicly and freely available to the research community. The work is expected to stimulate more interest and draw attention from the computer vision and multimedia communities to the fast-growing SEM application area

Geotechnical strategy and tactics at Anglo Platinum's PPRust open pit operation, Limpopo Province, South Africa

Over the last four years Potgietersrust Platinums (PPRust) has successfully implemented new geotechnical strategy and tactics to reduce risk, improving safety but also maximising profitability. A large database of core logging, face mapping and rock testing has been assembled and used in the slope design process. The data has also been used for optimising blast designs on a daily basis through the use of a geotechnical block model. This greatly improves blast fragmentation and therefore loading and milling efficiencies. Slope management includes a limit blasting programme, daily visual inspections, and state-of-the-art slope monitoring equipment, namely GroundProbe radar, Riegl lasers and GeoMoS automated prism monitoring. Slope optimisation incorporates all the field data, operational controls, cost of failure, full economic analysis of various slope angles and fault tree analysis. Savings on waste stripping of hundreds of millions of Rands were gained from the optimisation as slope angles could be increased due to improved geotechnical knowledge and management. PPRust’s geotechnical work is considered the benchmark for Anglo American open pit operations