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Mine Machine Radar Sensor for Emergency Escape

CSIRO, Technology Court, Pullenvale QLD 4069, Australia
Simtars, Robert Smith St Redbank, Queensland 4300, Australia
Author to whom correspondence should be addressed.
Resources 2020, 9(2), 16;
Received: 5 December 2019 / Revised: 17 January 2020 / Accepted: 22 January 2020 / Published: 4 February 2020
(This article belongs to the Special Issue Advances in Mining Technology: The Digital Mine)
This paper presents the results of recent work to develop and trial a mine machine radar sensor for underground coal mine vehicles. There is an urgent industry need for an integrated solution to the problem of operating an underground vehicle in conditions of dense ambient dust and/or smoke, such as may occur in underground coal mines after a fire or explosion. Under these conditions, sensors such as cameras and lidar offer limited assistance due to their inability to penetrate thick dust. Thermal infrared can penetrate dust but still results in poor vision, as there is insufficient temperature contrast between the tunnel walls and the ambient air. Microwave radar sensors are able to penetrate the dust, and suitable radar sensors have been developed for use in the automation industry. Adapting such sensors for use in an underground coal mining environment was the focus of this research effort, and involved trialing a suitable sensor in dust and smoke chambers as well as trials in an underground coal mine with introduced dust. Data processing and the development of a suitable user interface were key aspects of the research. Since any sensor would have to operate in an explosive atmosphere, a related research work developed a flameproof dielectric enclosure to allow the use of the radar in the mine environment. View Full-Text
Keywords: mining; underground; radar; sensor; dust; vehicle; navigation; guidance mining; underground; radar; sensor; dust; vehicle; navigation; guidance
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Hargrave, C.; Munday, L.; Kennedy, G.; de Kock, A. Mine Machine Radar Sensor for Emergency Escape. Resources 2020, 9, 16.

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