Characterization of Respirable Dust Generated from Full-Scale Laboratory Igneous Rock Cutting Tests with Conical Picks at Two Stages of Wear
Respirable dust poses long-term health issues to personnel working in mining and civil projects where mechanized mining and tunneling machines are used for hard rock excavation. Machines, such as longwall shearers, roadheaders, or continuous miners, use consumable picks to cut rock. However, rock du...
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Veröffentlicht in: | Minerals & metallurgical processing 2022-08, Vol.39 (4), p.1801-1809 |
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Sprache: | eng |
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Zusammenfassung: | Respirable dust poses long-term health issues to personnel working in mining and civil projects where mechanized mining and tunneling machines are used for hard rock excavation. Machines, such as longwall shearers, roadheaders, or continuous miners, use consumable picks to cut rock. However, rock dust is generated in the work environment each time the pick tip contacts the rock surface. Additionally, the generated dust can be reintroduced into the air further down in production, such as at transfer points. The purpose of this study is to characterize respirable dust particles generated at the pick tip at two stages of pick wear: new and moderately worn. Understanding dust characteristics in terms of concentration, size distribution, and particle shape throughout the life-cycle of the pick will provide a basis to mine and tunnel operators for changing out picks to mitigate dust generation at the source. This paper discusses the dust characteristics generated from preliminary full-scale cutting tests in a laboratory of an igneous rock block cut with conical picks at new and moderately worn levels of wear. The moderately worn pick generated a size distribution that favored smaller particle sizes compared to the new pick. The moderately worn pick also generated more overall dust, as the concentration level in mg/m
3
was over double the amount of the new pick. Lastly, both picks generated particles that had similar aspect ratios and roundness measures. |
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ISSN: | 2524-3462 2524-3470 |
DOI: | 10.1007/s42461-022-00625-w |