摘要
针对金属矿山露天采场采空区地球物理探测异常快速安全评价的技术难题,根据模糊数学理论,结合多年的采空区探测研究成果,在采空区类型划分和地球物理识别特征的基础上,基于GIS平台建立了综合高密度电阻率法、瞬变电磁法和地震映像法的7个采空区异常评价指标体系,分别为G1R、G2T、G3H、S1R、S2T、S3H和D1W。通过数据提取和重构技术对7个采空区异常评价指标进行了分级分类的数据标准化处理,并利用模糊数学分类计算模型对其进行了概率化赋值,构建了采空区异常指标模糊数学综合评价模型,实现了采空区异常评价的定量化和智能化。研究表明:基于模糊数学理论的采空区异常指标综合评价可以将传统的采空区异常圈定误差由±5.0 m提高到±2.0 m以内,并且可以实现采空区圈定的数字化、流程化和智能化,适合对海量不确定性的地球物理异常数据的快速处理和智能化评价。
For the technical difficulties of rapid and safe evalution of geophysical prospecting anomalies of the goaf inopen-pit of metal mines,guided by fuzzy mathematics theory,combined with the research results of goaf detection for manyyears and the classification of goafs and geophysical features,based on the GIS platform,seven goaf anomaly evaluation indexsystems based on high density resistivity method,transient electromagnetic method and seismic mapping method are estab-lished,which are G1R,G2T,G3H,S1R,S2T,S3Hand D1W.The data extraction and reconstruction techniques were used to classifythe data of the seven goaf anomaly evalution indexs,and the fuzzy mathematics classification calculation model was used toprobabilize the values.Then the fuzzy mathematics comprehensive evalution model of goaf anomaly index is constructed to real-ize the quantification and intelligence of goaf anomaly evaluation.The study results indicate that the comprehensive evalutionof the abnormal indicator of goaf based on fuzzy mathematics can increase the abnormal error of the traditional goaf from ±5.0 m to ±2.0 m,and it can realize the digitization,process and intelligence of the demarcation,and is suitable for the rapid pro-cessing and intelligent evaluation of massive geophysical anomaly data.
作者
贾三石
付建飞
王恩德
郭凯
门业凯
Jia Sanshi;Fu Jianfei;Wang Ende;Guo Kai;Men Yekai(School of Resource and Materials,Northeastern University at Qinhuangdao,Qinhuangdao 066004,China;School of Resources and Civil Engineering,Northeastern University,Shenyang 110819,China)
出处
《金属矿山》
CAS
北大核心
2020年第1期63-72,共10页
Metal Mine
基金
“十三五”国家重点研发计划项目(编号:2016YFC0801603)
关键词
露天铁矿
采空区
地球物理探测
数据重构
模糊数学
Open-pit iron mine
Goaf
Geophysical prospecting
Data reconstruction
Fuzzy mathematics