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朱海成, 韩新平, 冀常鹏, 章征成, 那忠武. 钻孔岩性识别条件下的数字爆破技术研究[J]. 煤炭科学技术, 2018, (10).
引用本文: 朱海成, 韩新平, 冀常鹏, 章征成, 那忠武. 钻孔岩性识别条件下的数字爆破技术研究[J]. 煤炭科学技术, 2018, (10).
ZHU Haicheng, HAN Xinping, JIN Changpeng, ZHANG Zhengcheng, NA Zhongwu. Research on digital blasting technique with lithology identification of borehole[J]. COAL SCIENCE AND TECHNOLOGY, 2018, (10).
Citation: ZHU Haicheng, HAN Xinping, JIN Changpeng, ZHANG Zhengcheng, NA Zhongwu. Research on digital blasting technique with lithology identification of borehole[J]. COAL SCIENCE AND TECHNOLOGY, 2018, (10).

钻孔岩性识别条件下的数字爆破技术研究

Research on digital blasting technique with lithology identification of borehole

  • 摘要: 为了实现露天矿山爆破作业过程的数字化精细爆破,钻孔的岩性识别、爆破装药专家系统是亟待解决的问题,而钻孔的实时岩性识别是诸问题中的关键问题。本研究基于LWD200型全液压矿用钻机,采用其现场实地的自学习功能,提取钻机钻进不同岩层对应的诸多指标;通过现场获取的大量岩性识别数据,运用现代数学方法对其进行处理,构建出在一定置信度条件下的诸指标与岩性的关系。之后取消自学习功能进入自动岩性识别工作状态,实现钻机进行钻进的过程中实时的岩性及位置的采集。通过远程传输至设计平台进行数字爆破设计,实现数字化精细爆破。

     

    Abstract: In order to realize the digital fine blasting in the explosive operations of open pit,the establishment of an expert system of blast charge and lithologic identification of borehole is the problem urgently to be solved. Based on LWD200 full hydraulic drilling rig,the present study used its self-learning function in site to collect various indexes during drilling in different strata. Using the modern mathematical method to analyze the large amounts of lithologic identification data obtained in site,the relation between the indexes and lithology with certain confidence level was established. Then the state of self-learning function is switched to the state of automatic lithologic identification to gather the data of lithology and location in real time during the drilling process. Finally,the above data was transmitted remotely to the digital blasting design platform to realize the digital fine blasting

     

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