摘要
岩体完整性是评价岩体质量的重要指标,弹性波勘探技术是实现这一目标的有效方法之一。为了克服传统评价过程中采用经验公式存在主观性过强和精细度不够的问题,基于岩体对穿声波波速数据,采用加权随机森林方法(weightedrandomforests,WRF)提出了一种新的多尺度岩体完整性评价指标(multi-scalerockmassintegrity index,MRMII)和相应的分析方法。该指标综合考虑了不同孔深对穿声波波速、卸荷状况、水文地质、埋深和岩性等关键参数,由WRF模型预测结果中的各类岩体完整性所占比例计算得出。通过实际工程应用,MRMII值与勘探数据吻合良好,并且能够对岩体完整性进行不同尺度的精细化评价。此外,相较于传统弹性波测试方法,该指标可以减小测量误差和工程师经验不足对分类结果的影响,获得更适合指导工程建设的评价分析结果。
Rock mass integrity,which can be obtained effectively according P-wave velocity,is an important factor for evaluating rock mass quality.To overcome the problems of too much subjectivity and insufficient precision in the traditional evaluation process using empirical formulas,a new multi-scale rock mass integrity index(MRMII)and corresponding evaluation method are proposed based on weighted random forest(WRF)algorithm and P-wave velocity data.The MRMII,comprehensively considering various key parameters such as the P-wave velocity along the hole depth,unloading conditions,hydrogeology,buried depth and lithology,is calculated by the proportions of various rock mass integrality in WRF model prediction results.An actual engineering application shows that the calculation values of the MRMII are consistent with the field surveys,showing that the MRMII can be used to refine evaluation of rock mass integrity in different scales.In addition,compared with the traditional P-wave testing method,the MRMII can reduce the impact of measurement errors and insufficient engineer experience on classification results and obtain more suitable results for guiding engineering construction.
作者
李明超
史博文
韩帅
王刚
LI Mingchao;SHI Bowen;HAN Shuai;WANG Gang(State Key Laboratory of Hydraulic Engineering Simulation and Safety,Tianjin University,Tianjin 300350,China;Chengdu Engineering Corporation Limited,PowerChina,Chengdu,Sichuan 610072,China)
出处
《岩石力学与工程学报》
EI
CAS
CSCD
北大核心
2020年第10期2060-2068,共9页
Chinese Journal of Rock Mechanics and Engineering
基金
天津市杰出青年科学基金资助项目(17JCJQJC44000)
国家优秀青年科学基金资助项目(51622904)。
关键词
岩石力学
岩体完整性
评价指标
对穿声波波速
加权随机森林
多尺度
精细分级
rock mechanics
rock mass integrity
evaluation index
P-wave velocity
weighted random forest
multi-scale
fine classification