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基于LM BP算法的隧道爆破振动灾害预测的应用
引用本文:蒋莉,黄华东,王先义,陈桦深.基于LM BP算法的隧道爆破振动灾害预测的应用[J].隧道建设,2016,36(5):525-530.
作者姓名:蒋莉  黄华东  王先义  陈桦深
作者单位:(1. 重庆市市政设计研究院, 重庆 400020; 2. 重庆交通大学土木工程学院, 重庆 400074; 3. 福建博海工程技术有限公司, 福建福州 350012)
基金项目:重庆铁路枢纽复杂环境岩石路堑与浅埋隧道安全控爆技术(2013Y080)
摘    要:为了对隧道爆破振动灾害的危险状态进行有效地预测,实验采用基于Levenberg Marquardt(LM)算法改进的BP算法,建立以实测隧道爆破掏槽眼装药量、爆心距和爆破振速为主要爆破影响因素的神经网络模型,对振速进行预测分析,预测结果与实测数据吻合良好;继而引用GB 6722—2014《爆破安全规程》所规定的临界安全振速反向预测掏槽装药量,通过反向预测计算得出满足安全振速要求的临界掏槽装药量。预测结果表明: LM BP算法相比传统的经验模型在振速预测上表现更好,通过反向的预测运算,能有效预知临界装药参数,对爆破振动安全预测及控制有积极的意义。

关 键 词:Levenberg  Marquardt算法  BP神经网络  隧道爆破振动  灾害预测
收稿时间:2015-11-02

Application of Tunnel Blasting Vibration Disaster Prediction Based on LM BP Neural Network
JIANG Li,HUANG Huadong,WANG Xianyi,CHEN Huashen.Application of Tunnel Blasting Vibration Disaster Prediction Based on LM BP Neural Network[J].Tunnel Construction,2016,36(5):525-530.
Authors:JIANG Li  HUANG Huadong  WANG Xianyi  CHEN Huashen
Institution:(1. Chongqing Municipal Administration Design and Research Institute, Chongqing 400020, China; 2. College of Civil Engineering, Chongqing Jiaotong University, Chongqing 400074, China; 3. Fujian Bo Hai Engineering Technology Co., Ltd., Fuzhou 350012, Fujian, China)
Abstract:The BP neural network model, with charging amount of blasting cut, blasting center distance and blasting velocity as main factors, is established based on Leyenberg Marquardt (LM) calculation method; and the blasting vibration velocity is predicted and analyzed. The charging amount of blasting cut is calculated by means of critical blasting vibration velocity in related criteria. The calculation results show that LM BP neural network method is superior to traditional method in terms of prediction of blasting vibration velocity; the blasting cut charging amount calculated by means of critical blasting vibration velocity inverse calculation method is rational and effective.
Keywords:Levenberg Marquardt calculation  BP neural networks  tunnel blasting vibration  disaster prediction
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