基于数值模拟的某大型磷锰矿边坡稳定性分析与地质灾害预防研究  

Stability Analysis and Geological Disaster Prevention of Large-scale Phosphorus Manganese Mine Slope Based on Numerical Simulation

作　　者：赵鹏[1,2] 马晓博 刘锐剑 ZHAO Peng;MA Xiaobo;LIU Ruijian(Beijing University of Chemical Technology,Beijing 102202,China;Hebei Province Alum Mountain Phosphate Mining Co.,Zhangjiakou,Hebei 075641,China)

机构地区：[1]北京化工大学,北京102202 [2]河北省矾山磷矿有限公司,河北张家口075641

出　　处：《中国锰业》2025年第1期103-108,共6页China Manganese Industry

摘　　要：边坡稳定性分析是地质灾害预防的关键,为提高边坡稳定性分析的准确性,基于数值模拟技术,提出了一种结合小波变换和断面数据校正的改进型时移高密度电法,通过该方法进行正反演数值模拟能够有效识别边坡的潜在失稳区域。实验结果显示,小波变换降噪准确率为92.3%,比经验模态分解和傅里叶变换分别高84.6%、46.5%,并且小波变换降噪后的电阻率等值线图伪影减少了86.3%,可以提高高密度电法收集电场信息的准确性。研究方法进行正反演的结果图可以呈现出断层区域的电阻率变化,有利于边坡稳定性分析和灾害预防。该数值模拟方法为大型磷锰矿边坡灾害预防提供了一种新的技术。Slope stability analysis is crucial for preventing geological disasters.This study aims to enhance the accuracy of slope stability analysis using an improved time-shift high-density electrical method combining wavelet transform and section data correction.Forward and inverse numerical simulations using this method can effectively identify potential slope instability regions.Experimental results indicate that wavelet transform achieves a 92.3%denoising accuracy,surpassing empirical mode decomposition(84.6%higher)and Fourier transform(46.5%higher).Wavelet-transform-based denoising reduces resistivity contour map artifacts by 86.3%,enhancing the accuracy of electric field data collected by electrical resistivity imaging(ERI).Forward and inverse modeling results reveal resistivity variations in fault zones,aiding slope stability analysis and disaster prevention.This numerical simulation approach offers a novel technique for preventing slope disasters in large-scale phosphorus manganese mines.

关 键 词：高密度电法 边坡 地质结构 降噪 数值模拟 

分 类 号：P633[天文地球—地质矿产勘探]