| 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. |
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