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TBM破岩刀盘振动表征参数研究 被引量:3

Study on Vibration Characterization Parameters of TBM Rock-breaking Cutterhead
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摘要 TBM破岩过程中,刀盘不可避免会产生强烈振动。刀盘振动响应是岩-机相互作用的结果,可以作为岩体识别、掘进参数优化的重要依据。针对刀盘振动这一多源参数影响信号,挖掘其内含信息尤其重要。根据TBM掘进试验数据,分析了时间对振动特征分布的影响,构建了多维振动特征与掘进参数的随机森林模型,通过其特征重要性评价功能筛选了能敏感反映掘进参数变化的振动特征。研究结果表明,现场振动监测应至少达到刀盘旋转一周的时长,在该时长下各振动特征分布趋于稳定;峰值因子、频率标准差是最能反映推力、转速变化的特征,可以作为研究振动信号与掘进参数变化关系的关键特征。 During the TBM rock breaking process,it is inevitable to generate strong vibration on the cutterhead.The vibration response of the cutterhead is the result of the interaction between rock and TBM,and it can serve as an important basis for rock mass identification and tunnelling parameter optimization.It is particularly important to obtain the information contained in this multi-source vibration signal of the cutterhead.Based on the TBM tunnelling test data,the influence of time on the distribution of vibration features is analyzed,a random forest model of multi-dimensional vibration features and tunnelling parameters is constructed,and the vibration features that can respond sensitively to changes in tunnelling parameters are screened through its feature importance evaluation function.The research results indicate that on-site vibration monitoring duration should reach at least one rotation period of the cutterhead,during which the distribution of various vibration characteristics tends to be stable.Peak factor and frequency standard deviation are the features that can best respond to changes in thrust and rotation speed,and can be used as key features for studying the relationship between vibration signal and change in tunnelling parameters.
作者 刘东鑫 肖禹航 周小雄 龚秋明 刘俊豪 LIU Dongxin;XIAO Yuhang;ZHOU Xiaoxiong;GONG Qiuming;LIU Junhao(Key Laboratory of Urban Disaster Prevention and Mitigation of Ministry of Education,Beijing University of Technology,Beijing 100124;China Construction Infrastructure Co.,Ltd.,Beijing 100037;State Key Laboratory of Water and Sediment Science and Water Conservancy and Hydropower Engineering,Tsinghua University,Beijing 100084)
出处 《现代隧道技术》 CSCD 北大核心 2023年第4期153-162,共10页 Modern Tunnelling Technology
关键词 TBM 刀盘振动响应 掘进试验数据 信号处理 振动特征选择 TBM Cutter vibration response Tunnelling test data Signal processing Vibration feature selection
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