大连极硬岩地层复合盾构刀具磨损的分析与预测

发布时间：2018-07-16 14:58

【摘要】：刀具磨损是盾构在极硬岩地层中施工遇到的难题之一,因此对刀具磨损的分析与预测对盾构施工意义重大。通过对大连地铁一号线101标段港湾广场站~中山广场站区间隧道盾构刀具进行磨损监测,利用偏最小二乘回归法,对在不同盾构掘进情况下刀具磨损的多组数据进行分析。根据自变量载荷因子情况,分别选取刀具磨损量为因变量,盾构机的贯入度p、推进速度v、刀盘转速n、盾构推力F、盾构扭矩T、土仓压力Ps、刀具半径L等掘进参数为自变量,选用部分自变量和全部自变量组合用于建模,并建立了偏最小二乘回归模型。筛选样本数据和全部样本数据,分别对建立的刀具磨损模型进行验证,并通过已有数据对刀具磨损进行分析与预测。研究结论表明在极硬岩地层中采用偏最小二乘法可以比较合理地选择自变量,同时建立的数学模型也能较好地对不同盾构掘进情况下的刀具磨损进行计算。
[Abstract]:Tool wear is one of the difficult problems encountered in the construction of shield tunneling in extremely hard rock strata, so the analysis and prediction of tool wear is of great significance to shield construction. By monitoring the wear of shield cutting tools in the tunnel between Haven Square Station and Zhongshan Square Station of Dalian Metro Line 1, the multi-group data of tool wear under different shield tunneling conditions are analyzed by using partial least square regression method. According to the load factors of independent variables, the tool wear is selected as dependent variable, and the tunneling parameters such as penetration p, propelling speed v, speed of cutter head n, shield thrust F, shield torque T, earth bin pressure Ps and tool radius L are selected as independent variables. Partial independent variables and all independent variables are selected for modeling and partial least square regression model is established. The tool wear model was verified by screening the sample data and all the sample data, and the tool wear was analyzed and predicted by the existing data. The results show that the partial least square method can be used to select the independent variables reasonably and the mathematical model can also be used to calculate the tool wear under different shield tunneling conditions.
【作者单位】：北京交通大学;
【基金】：国家自然科学基金资助项目(51178027)
【分类号】：U455.39

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