基于BP网络的深部软岩巷道围岩力学参数反演研究.pdf

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1、第33卷第5期矿冶工程V01．33№52013年1O月MININGANDMETALLURGICALENGINEERING0ctober2013基于BP网络的深部软岩巷道围岩力学参数反演研究①夏海燕，付建军，时凯(1．湖北工程学院城市建设学院，湖jE武汉410073；2．中国水电顾问集团中南勘测设计研究院，湖南长沙4100142；3．中国科学院武汉岩土力学研究所，湖北武汉430071)摘要：为探索高地应力下深部软岩巷道围岩应力场及位移场的分布情况，建立了简化的应变软化模型，分析了此模型的关键参数；采用均匀设计法设计了数值计算中待分析的参数方案，且将各方案参数代入FLAC软

2、件中进行了数值仿真分析；再将各工况下监测点计算的相对位移与岩体力学参数代人BP网络进行训练、学习，并将监测点位移相对监值输入训练的BP网络，获得参数反演值。以淮南矿业集团顾桥煤矿轨道巷为工程背景，进行了巷道深部位移监测，根据监测结果反演了简化应变软化模型的关键参数，经正分析对比验证了力学参数反演结果的准确度、可靠性，反演结果为后续工程数值计算奠定了基础。关键词：软岩巷道；围岩；高应力；应变软化模型；均匀设计；BP网络中图分类号：TU443文献标识码：Adoi：10．3969／j．issn．0253-6099．2013．05．006文章编号：0253-6099(2013)

3、05—0025—05StudyonParametricInversionofRockMechanicsforSurroundingRockinDeepSoftRockRoadwaybyBPNeuralNetworkMethodXIAHai．yan，FUJian-jun，SHIKai(1．CollegeofUrbanConstruction，HubeiEngineeringUniversity，Wuhan410073，Hubei，China；2．HYDROCHINAZhongnanEngineeringCorporation，Changsha410014，Hunan，Ch

4、ina；3．InstituteofRockandSoilMechanics，ChineseAcademyofSciences，Wuhan430071，Hubei，China)Abstract：Inordertoexplorethefieldofstressanddisplacementfieldofthesurroundingrockindeepsoftrockroadwayundertheconditionofhighstressandlowstrength，asimplifiedstrain-softeningmodelwasestablishedandkeypar

5、ametersofthismodelwereanalyzed．Theparameterprogramtobeanalyzedinnumericalcomputationwasdesignedwithauniformdesignmethod，thenofwhichallparametersweresubstitutedintoFLAC。。softwarefornumericalsimulationanalysis．Afterthat，therelativedisplacementandrockmassmechanicalparametersofeachmonitoring

6、pointunderdifferentworkingconditionsweresubstitutedintoBPneuralnetwork，fortrainingandstudy，thendisplacementrelativetomonitoringwasinputintothetrainedBPneuralnetworktoobtaintherealparameters．WiththesoftrockroadwayinGuqiaoCoalMineofHuainanMiningGroupasanengineeringpractice，keyparametersint

7、hesimplifiedstrain-softeningmodelwereprocessedbyparametricinversionbasedonin-situmonitoringofthedeepdisplacementofsuroundingrock．Theresuhhasbeenverifiedtobeaccurateandreliableafteranalysisandcomparison，layingthegroundworkforthefollowingengineeringnumericalanalysis．Keyword