{"title":"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","authors":"Lesego Senjoba, Hajime Ikeda, Hisatoshi Toriya, Tsuyoshi Adachi, Youhei Kawamura","doi":"10.1080/17480930.2024.2372508","DOIUrl":null,"url":null,"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 ...","PeriodicalId":49180,"journal":{"name":"International Journal of Mining Reclamation and Environment","volume":"50 1","pages":""},"PeriodicalIF":2.7000,"publicationDate":"2024-06-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Deep learning-based rock type identification using drill vibration frequency spectrum images\",\"authors\":\"Lesego Senjoba, Hajime Ikeda, Hisatoshi Toriya, Tsuyoshi Adachi, Youhei Kawamura\",\"doi\":\"10.1080/17480930.2024.2372508\",\"DOIUrl\":null,\"url\":null,\"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 ...\",\"PeriodicalId\":49180,\"journal\":{\"name\":\"International Journal of Mining Reclamation and Environment\",\"volume\":\"50 1\",\"pages\":\"\"},\"PeriodicalIF\":2.7000,\"publicationDate\":\"2024-06-28\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"International Journal of Mining Reclamation and Environment\",\"FirstCategoryId\":\"5\",\"ListUrlMain\":\"https://doi.org/10.1080/17480930.2024.2372508\",\"RegionNum\":3,\"RegionCategory\":\"工程技术\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q3\",\"JCRName\":\"ENVIRONMENTAL SCIENCES\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"International Journal of Mining Reclamation and Environment","FirstCategoryId":"5","ListUrlMain":"https://doi.org/10.1080/17480930.2024.2372508","RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"ENVIRONMENTAL SCIENCES","Score":null,"Total":0}
Deep learning-based rock type identification using drill vibration frequency spectrum images
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 ...
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