| 利用神经网络法预测风动潜孔锤钻速 |
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| 引用本文： | 朴金石,殷琨,范黎明.利用神经网络法预测风动潜孔锤钻速[J].吉林大学学报(地球科学版),2009,39(5):882-886. |
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| 作者姓名： | 朴金石 殷琨 范黎明 |
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| 作者单位： | 吉林大学 建设工程学院,长春130061 |
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| 基金项目： | 中国地质调查局区域地质调查项目，吉林大学"985"工程研究生创新基金项目 |
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| 摘 要： | 风动潜孔锤钻进在钻效方面有着传统钻进方法无可比拟的优势。以往的钻速预测主要是针对回转钻进，而准确预测风动潜孔锤钻速则更具有现实意义，更有利于合理制定钻井计划。利用有多隐层的BP神经网络原理，综合考虑钻压、转速、风压、风量、钻井深度、钻头工作时间等各方面参数对钻速的影响，研究了贯通式潜孔锤冲击回转钻井钻速的预测方法，并对现场实际钻井作业进行了预测。预测结果与现场实际情况能很好地吻合。同时又以预测结果为基础，优选钻进参数以指导施工。
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| 关 键 词： | 神经网络 钻速 冲击回转钻进 风动潜孔锤 |
| 收稿时间： | 2009-04-01 |
Neural Network Method in the Penetration Rate Prediction of Percussive Drilling |
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| PIAO Jin-shi,YIN Kun,FAN Li-ming.Neural Network Method in the Penetration Rate Prediction of Percussive Drilling[J].Journal of Jilin Unviersity:Earth Science Edition,2009,39(5):882-886. |
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| Authors: | PIAO Jin-shi YIN Kun FAN Li-ming |
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| Institution: | College of Construction Engineering|Jilin University|Changchun 130061| China |
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| Abstract: | Percussive drilling has an incomparably priority to traditional rotary drilling methods in the aspect of penetration efficiency and the previous prediction of the drilling rate is only refered to rotary drilling.Practically,accurate prediction of the rate of penetration(ROP) of percussive drilling is very important in that it can help make the planning of the rock excavation projects in high efficiency.The multilayer neural network with back propagation algorithm(BPNN) has been employed to analyze the influ... |
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| Keywords: | neural network the rate of penetration(ROP) percussive rotary drilling DTH hammer |
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