Deep learning-based rock type identification using drill vibration frequency spectrum images

IF 2.7 3区工程技术 Q3 ENVIRONMENTAL SCIENCES

International Journal of Mining Reclamation and Environment Pub Date : 2024-06-28 DOI:10.1080/17480930.2024.2372508

Lesego Senjoba, Hajime Ikeda, Hisatoshi Toriya, Tsuyoshi Adachi, Youhei Kawamura

引用次数: 0

Abstract

Rock identification is crucial in the mining industry. It provides useful information regarding the geological characteristics of an area, which can be applied to drill-bit selection, optimisation ...

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利用钻机振动频谱图像进行基于深度学习的岩石类型识别

岩石识别在采矿业中至关重要。它提供了有关某一区域地质特征的有用信息，这些信息可用于钻头选择、优化 ...

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

International Journal of Mining Reclamation and Environment ENVIRONMENTAL SCIENCES-MINING & MINERAL PROCESSING

CiteScore

5.70

自引率

8.30%

发文量

审稿时长

>12 weeks

期刊介绍： The International Journal of Mining, Reclamation and Environment published research on mining and environmental technology engineering relating to metalliferous deposits, coal, oil sands, and industrial minerals. We welcome environmental mining research papers that explore: -Mining environmental impact assessment and permitting- Mining and processing technologies- Mining waste management and waste minimization practices in mining- Mine site closure- Mining decommissioning and reclamation- Acid mine drainage. The International Journal of Mining, Reclamation and Environment welcomes mining research papers that explore: -Design of surface and underground mines (economics, geotechnical, production scheduling, ventilation)- Mine planning and optimization- Mining geostatics- Mine drilling and blasting technologies- Mining material handling systems- Mine equipment