[1]马海越①②,张云鹏①②,刘宏颖①②.基于BP神经网络的地下采场爆破振速预测[J].爆破器材,2019,48(06):55-59.[doi:10.3969/j.issn.1001-8352.2019.06.011]
　MA Haiyue,ZHANG Yunpeng,LIU Hongying.Prediction of Blasting Vibration Velocity in Underground Stope Based on BP Neural Network[J].EXPLOSIVE MATERIALS,2019,48(06):55-59.[doi:10.3969/j.issn.1001-8352.2019.06.011]
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基于BP神经网络的地下采场爆破振速预测()
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《爆破器材》[ISSN:1001-8352/CN:32-1163/TJ]

卷:
48
期数:
2019年06
页码:
55-59
栏目:
爆破技术
出版日期:
2019-12-09

文章信息/Info

Title:
Prediction of Blasting Vibration Velocity in Underground Stope Based on BP Neural Network
文章编号:
5365
作者:
马海越①②; 张云鹏①②; 刘宏颖①②
①华北理工大学河北省矿业开发与技术重点实验室（河北唐山，063210）
②华北理工大学矿业工程学院（河北唐山，063210）
Author(s):
MA Haiyue①②;  ZHANG Yunpeng①②; LIU Hongying①②
①Mining Development and Safety Technology Key Laboratory, North China University of Science and Technology (Hebei Tangshan, 063210)
②College of Mining Engineering, North China University of Science and Technology (Hebei Tangshan, 063210)
关键词:
BP神经网络; 爆破振动; 地下采场; 振速预测
Keywords:
back-propagation network;  blasting vibration;  underground stope;  vibration velocity prediction
分类号:
TD235.1
DOI:
10.3969/j.issn.1001-8352.2019.06.011
文献标志码:
A
摘要:
为降低矿石开采中爆破振动的危害并达到最佳爆破效果，以河北唐山某矿山地下采场－156 m阶段爆破开采为例，采集了爆破振动监测数据，运用BP神经网络与萨道夫斯基经验公式分别对爆破峰值振速进行预测。结果表明：BP神经网络平均误差为17.22%；萨氏公式平均误差为40.76%。BP神经网络预测地下采场爆破振速是可行的。
Abstract:
In order to eliminate the harm of blasting vibration and achieve the optimum blasting effect, blasting vibration velocity at －156 m stage in an underground stope of Tangshan was predicted and studied. Monitoring data of blasting vibration were collected, and the peak value of blasting vibration was predicted by BP (back-propagation) network model and Sadov’s Formula. The results show that the average error of BP neural network is 17.22%, and the average error of Sadov’s Formula is 40.76%. It is feasible to use BP neural network method to predict the blasting vibration velocity of underground stope.

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备注/Memo

备注/Memo:
收稿日期：2019-05-17
基金项目：河北省自然科学基金项目(E2016209388) ；河北省教育厅项目（ZD2015020）
第一作者：马海越（1994－），男，硕士，主要从事安全管理与评价等研究。E-mail：1309132@163.com
更新日期/Last Update: 2019-12-04