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作 者:李翰智 Li Hanzhi(Jinneng Holding Coal Industry Group Majiliang Mining Machine Excavation Team 2,Datong Shanxi 037000,China)
机构地区:[1]晋能控股煤业集团马脊梁矿机掘二队,山西大同037000
出 处:《山西化工》2024年第7期192-194,共3页Shanxi Chemical Industry
摘 要:鉴于某煤矿60采区0420工作面掘进工程中存在人工效率慢的缺点,同时为了解决掘进难度高和不合理的爆破方式,基于BP神经网络设计,优化爆破参数,建立模型结构,进行现场试验,结果表明:工作面爆破开挖后,巷道成形基本保持完整,少数局部有超挖现象,数值都控制在100 mm以内,提高了掘进效率,保证了爆破效果。In view of the slow manual efficiency in the excavation project of the 0420 working face in the 60 mining area of a certain coal mine,and in order to solve the high difficulty of excavation and unreasonable blasting methods,based on the design of BP neural network,the blasting parameters were optimized,the model structure was established,and on-site experiments were conducted.The results showed that after the blasting excavation of the working face,the formation of the roadway remained basically intact,with a few local overexcavation phenomena,and the values were controlled within 100 mm,which improved the excavation efficiency and ensured the blasting effect.
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