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Longwall automation:trends,challenges and opportunities

International Journal of Mining Science and Technology 2017年第5期27卷 733-739页

作者： Jonathon C.Ralston chad o.hargrave Mark T.Dunn Coal Mining Research Program CSIRO EnergyBrisbaneAustralia

This paper explores the ongoing development and implementation of longwall automation technology to achieve greater levels of underground coal mining performance. The primary driver behind the research and development effort is to increase the safety, productivity and efficiency of longwall mining operations to enhance the underlying mining business. A brief review of major longwall automation challenges is given followed by a review of the insights and benefits associated with the LASC longwall shearer automation solution. Areas of technical challenge in sensing, decision support, autonomy and human interaction are then highlighted, with specific attention given to remote operating centres, proximity detection and systems-level architectures in order to motivate further automation system *** vision for a fully integrated coal mining ecosystem is discussed with the goal of delivering a highperformance, zero-exposure and environmentally coherent mining operations.

关键词： Safety Productivity Environment Mining automation Longwall mining Remote mining Sensing

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Infrastructure-based localisation of automated coal mining equipment

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International Journal of Coal Science & Technology 2017年第3期4卷 252-261页

作者： chad o. hargrave Craig A. James Jonathon C. Ralston Mining and Processing Technologies Research Group CoalMining Research Program CSIRO Energy BrisbaneAustralia

A novel radar-based system for longwall coal mine machine localisation is described. The system, based on a radar-ranging sensor and designed to localise mining equipment with respect to the mine tunnel gate road infrastructure, is developed and trialled in an underground coal mine. The challenges of reliable sensing in the mine environment are considered, and the use of a radar sensor for localisation is justified. The difficulties of achieving reliable positioning using only the radar sensor are examined. Several probabilistic data processing techniques are explored in order to estimate two key localisation parameters from a single radar signal, namely along-track position and across-track position, with respect to the gate road structures. For the case of across-track position, a conventional Kalman filter approach is sufficient to achieve a reliable estimate. However for along-track position estimation, specific infrastructure elements on the gate road rib-wall must be identified by a tracking algorithm. Due to complexities associated with this data processing problem, a novel visual analytics approach was explored in a 3D interactive display to facilitate identification of significant features for use in a classifier algorithm. Based on the classifier output, identified elements are used as location waypoints to provide a robust and accurate mining equipment localisation estimate.

关键词： Localisation · Waypoint navigation · Machine learning · Radar ·Underground · Longwall mining· Automation

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Sensing for advancing mining automation capability:A review of underground automation technology development

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International Journal of Mining Science and Technology 2014年第3期24卷 305-310页

作者： Ralston Jonathon Reid David hargrave chad Hainsworth David Earth Science and Resource Engineering Commonwealth Scientific and Industrial Research Organisation

This paper highlights the role of automation technologies for improving the safety, productivity, and environmental sustainability of underground coal mining processes. This is accomplished by reviewing the impact that the introduction of automation technology has made through the longwall shearer automation research program of Longwall Automation Steering Committee(LASC). This result has been achieved through close integration of sensing, processing, and control technologies into the longwall mining process. Key to the success of the automation solution has been the development of new sensing methods to accurately measure the location of longwall equipment and the spatial configuration of coal seam geology. The relevance of system interoperability and open communications standards for facilitating effective automation is also discussed. Importantly, the insights gained through the longwall automation development process are now leading to new technology transfer activity to benefit other underground mining processes.

关键词： Mining automation Longwal mining Longwal Automation Steering Committee Interoperability Inertial navigation Coal seam sensing

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