摘要
为研究露天矿内排土场工后沉降规律,定义内排土场下沉系数为地表最终沉降量与初始覆土高度的比值,并以内蒙古锡林浩特市胜利一号露天矿内排土场为研究区,利用41期高时间分辨率sentinel-1 A数据采用小基线集(SBAS)技术进行内排土场沉降监测,在此基础上引入混沌理论中的相空间重构理论结合二阶Volterra自适应滤波对沉降时间序列进行单步预测。结果表明:①内排土场沉降剖面呈现明显的半漏斗状,总体上累积沉降量与到矿坑的距离成反比,通过沉降时间序列分析可得Ⅰ,Ⅱ区域处于沉降活跃期,存在滑坡、泥石流风险,是后期沉降监测的重点区域,Ⅲ~Ⅶ区域步入稳定过渡期,Ⅷ区域已基本稳定,初步判断该区已基本满足了土地复垦及建设简单构筑物的基本要求。②经曲线拟合,得观测周期内,内排土场下沉系数约为0.639 cm/m。③经最大Lyapunov指数验证,通过SBAS技术得到的4组沉降量时间序列均具有混沌特征。④运用混沌理论中的相空间重构理论结合二阶Volterra自适应滤波对沉降量进行单步预测,预测结果显示其可在短期内较好地反应真实值变化趋势,前10步预测结果的平均绝对误差(MAE)、平均相对误差(MAPE)和均方根误差(RMSE)均在6%以下,但随预测步数的增加,预测精度逐渐下降,这表明二阶Volterra自适应滤波仅可用于SBAS获取的一维沉降观测数据的短期预测,将其应用于长期预测的结果不可靠。
In order to explore the settlement laws of inner dump in open pit after construction,the subsidence coefficient of inner dump is defined as the ratio of the final settlement of dump surface to the initial height of dump.The inner dump of Shengli No.1 Open-pit Mine in Xilinhot City,China,is taken as the research area in this study.Forty-one high temporal resolution sentinel-1A images are used to monitor the settlement of inner dump by using the small baseline subset(SBAS)technology.On this basis,the phase space reconstruction theory in the chaos theory and the second-order Volterra adaptive filtering are introduced to realize a sin-gle-step prediction of the settlement time series.The results show that①the subsidence profile of the inner dump is obviously semi-funnel-shaped,and the cumulative settlement is inversely proportional to the distance from the pit.Through the analysis of the subsidence time series,it can be concluded that the areas I and II are in the active period of subsidence,with the risk of landslide and debris flow.They are the key areas for the later subsidence monitoring.The areas III-VII enter the transition period.While the areaⅧhas been basically stable,the area basically meets the basic requirements of land reclamation and construction of simple structures.②By curve fitting,the subsidence coefficient of the inner dump is estimated to be 0.639 cm/m in the observation period.③Verified by the maximum Lyapunov index,the four sets of settlement time series ob-tained by SBAS technology all have chaotic characteristics.④The phase space reconstruction theory in the chaos theory and the second-order Volterra adaptive filtering are combined to realize a single-step prediction of the settlement time series.The prediction results show that it can better reflect the change trend of real value in a short time.The average absolute error(MAE),average relative error(MAPE)and root mean square error(RMSE)of the first ten prediction results are all below 6%,but with the increase of prediction steps,the
作者
田雨
雷少刚
卞正富
TIAN Yu;LEI Shaogang;BIAN Zhengfu(Institute of Land and Resources,China University of Mining and Technology,Xuzhou 221116,China;Engineering Research Center of Mine Ecological Construction,Ministry of Education,Xuzhou 221116,China)
出处
《煤炭学报》
EI
CAS
CSCD
北大核心
2019年第12期3865-3873,共9页
Journal of China Coal Society
基金
国家重点研发计划资助项目(2016YFC0501107)
国家重点基础研究发展计划(973)资助项目(2014FY110800)
