摘要
围岩稳定性受诸多因素的影响,各影响因素间存在复杂的非线性关系。为准确判定围岩稳定性类别,选取岩石质量指标RQD、岩石单轴饱和抗压强度Rw、完整性系数Kv、结构面强度系数Kf、地下水渗水量ω等作为影响围岩稳定性的主要因素,通过主成分分析(Principal Component Analysis,PCA)将以上5个影响因素降维成2个相互独立的主成分,采用相关向量机(Relevance Vector Machine,RVM)建立主成分变量与围岩稳定性类别之间的非线性映射关系,将输出的评价结果输入至"一对一"投票器以确定稳定性类别;将PCA-RVM围岩稳定性识别模型运用于实际工程,用21组样本对6组样本进行预测,其中5组预测结果与实际类别一致。结果表明:提出的识别模型适用于小样本问题,通过设置合理的带宽和迭代次数可有效提高模型精度,减少误判率。
The stability of tunnel surrounding rock is affected by many factors, and there are complex nonlinear relationships among various influencing factors. In order to accurately determine the surrounding rock stability category, five factors including rock quality index RQD, rock uniaxial saturated compressive strength Rw, integrity coefficient Kv, structural plane strength coefficient Kfand groundwater seepage ω are selected as the main factors affecting the stability of surrounding rock, through principal component analysis(PCA), we reduce the above influencing factors into two independent principal components, and use the relevance vector machine(RVM) to establish a nonlinear mapping relationship between the principal component variables and the surrounding rock stability categories. The results of the evaluation are entered into a"one-against-one"voter to determine the stability category. The PCA-RVM surrounding rock stability identification model is applied to actual projects, and 21 sets of samples are used to predict 6 sets of samples, of which 5 sets of prediction results are consistent with the actual category. The results show that the proposed recognition model is suitable for small sample problems. By setting an appropriate bandwidth and iteration times, the accuracy of the model can be effectively improved and the false positive rate can be reduced.
作者
张研
曾建斌
景小青
邓雪沁
ZHANG Yan;ZENG Jianbin;JING Xiaoqing;DENG Xueqin(Guangxi Key Laboratory of Geomechanics and Geotechnical Engineering,Guilin 541004,China;School of Civil and Architecture Engineering,Guilin University of Technology,Guilin 541004,China;Sinohydro Engineering Bureau 4 Co.,Ltd.,Xining 810007,China)
出处
《煤矿安全》
CAS
北大核心
2020年第11期274-280,共7页
Safety in Coal Mines
基金
国家自然科学基金资助项目(51409051)
广西岩土力学与工程重点实验室资助项目(桂科能19-Y-21-9)。
关键词
围岩稳定性
主成分分析
相关向量机
分类模型
识别模型
surrounding rock stability
principal component analysis
relevance vector machine
classification model
identification
作者简介
张研(1983-),河北张家口人,副教授,博士,2013年毕业于广西大学,研究方向为岩体力学、深部岩体工程安全性分析。
