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深孔爆破参数智能优化及爆破效应控制研究

Study on Intelligent Optimization of Deep-hole Blasting Parameters and the Control of Blasting Effects

【作者】 潘东

【导师】 周科平;

【作者基本信息】 中南大学 , 安全技术及工程, 2010, 硕士

【摘要】 结合云南卡房新山矿段试验采场工程实际,在应用“采矿环境再造连续采矿嗣后充填采矿法”工程背景下,采用深孔爆破是实现2000t产能的关键技术,本文重点着眼于深孔爆破参数智能优化及爆破效应控制研究。在传统爆破参数优化研究基础上应用多种优化方法相结合实现爆破参数智能优化,其中应用爆破漏斗试验、BP神经网络实现深孔爆破参数优化,此后进行现场爆破与监测试验和爆破动载荷作用数值模拟方法实现对爆破效应控制研究。本文就此开展了深入研究,主要完成了下述工作:(1)进行利文斯顿爆破漏斗现场试验;选取与试验采场岩体性质尽可能相近的岩体分别进行单孔爆破漏斗试验和变孔距多孔同段爆破漏斗试验,初步确定适合本项工程实际的爆破孔网参数。(2)基于BP人工神经网络的深孔爆破参数优化;在广泛收集国内外典型爆破漏斗试验数据的基础上,利用人工神经网络非线性、自适应和高精度等特点构建爆破参数优化模型,在现场试验的基础上进一步优化爆破孔网参数。(3)利用LS-DYNA对C5矿房爆破动载荷作用下采场强度响应进行数值模拟分析;以C5矿房为例,利用动力学软件进行动态载荷作用模拟,通过重点校核充填体动载荷作用下强度响应研究,确定起爆顺序、最大起爆药量、微差时间和爆破控制技术等爆破参数,实现对充填体的损伤效应研究。(4)试验采场C5矿房进行爆破放矿,并运用TC-4850爆破振动监测仪针对不同爆心距、不同高程差和主要保护对象进行实时监测试验,实现对爆破作用强度的控制研究。

【Abstract】 Based on the stope’s engineering practice of the test in Yunnan kafang xinshan section. Under the project background that mining environment regeneration continuous mining afterwards filling mining method. It is the key technology to achieve 2000t capacity by using medium-length hole blasting. This paper is focus on the intelligent optimization of deep-hole blasting parameters and the control of blasting effects. On the basis of the traditional researchment of blasting paramenter, combining a variety of optimization in order to realize the blasting paramenter for multi-boundary states. Such as crater test, bp neural network and blasting load. Then carry out the blasting and monitoring site test and implement the control of blasting effect. This subject carried out in-depth study on the following work:(1) Carry out Livingston blasting crater test. Select the rock whose rock behaviour is similar with the stope’s as possible to do single hole blasting crater test and variable hole distance porous with the same segment blasting test.Determine spacing pattern parameters which are suitable for thi engineering.(2) Deep-hole blasting parameters based on bp neural network.After collecting the crater test data abroad,using the nonlinear, adaptive and high accuracy characteristics of artificial neural network to construct blasting optimization.(3) Numerical Simulation Analysis on stope strength response by using LS-DYNA. For example C5 stope,using dynamics simulation software for dynamic load.By focusing on checking backfill strength of response under dynamic loading to determine initiation sequence,the maximum primary explosive,tiny difference time and blasting control technology. To achieve the research on damage effects of filling.(4) Stope C5 has blasted and drawing.By using TC-4850 blast vibration monitor to have real-time monitoring for different blast center distance,difference of elevation and the main object of protection. To achieve the research on the control of intensity of blasting.

  • 【网络出版投稿人】 中南大学
  • 【网络出版年期】2012年 02期
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