基于多层感知机技术的地铁盾构施工参数预测OACSTPCD
Prediction of subway shield construction parameters based on multi-layer perceptron
在地铁工程建设中,盾构法施工技术已经得到了广泛的应用,盾构掘进参数的合理预测对提高施工安全性及降低操作难度具有较大实际意义.以中国杭州机场快线地铁隧道某标段为工程背景,以隧道直径范围内土层摩擦角、黏聚力、压缩模量、重度以及隧道顶部埋深、盾构机预设刀盘转速、推进速度作为输入,以盾构施工时的注浆量、注浆压力、出土量、总推力和刀盘扭矩为输出,建立基于多层感知机的盾构掘进参数预测模型.通过对比不同超参数组合情况下的模型在数据集上的预测表现,挑选出适合于该工程盾构施工参数的预测模型.使用实测数据对模型预测效果进行验证,预测值与实测数据总体变化规律一致,平均误差在20%以内.建立的多层感知机模型预测结果较为合理,具有较好的预测精度,可用于复合地层条件下同类型盾构掘进参数的预测.
Shield construction technology has been widely used in subway construction,and reasonable prediction of shield tunneling parameters is of great practical significance for improving construction safety and reducing operational difficulties.Taking a section of the Hangzhou Airport Express Underpass Tunnel as the engineering background,this study uses the friction angle,cohesion force,compression modulus and heaviness of the soil layer within the diameter of the tunnel as well as the burial depth of the tunnel cover,the preset blade speed and propulsion speed of the shield machine as inputs,and the slurry volume,slurry pressure,soil discharge volume,total thrust force and blade torque during the shield construction as outputs,and establishes a prediction model of shield tunneling parameters based on a multi-layer perceptron.By comparing the predictive performance of the model under different combinations of hyper-parameters on the dataset,a suitable shield construction parameter prediction model is selected for the project.The model predictive effect is verified using the measured data,and the predicted values are consistent with the overall variation pattern of the measured data,with an average error within 20%.The established multi-layer perceptron model provides reasonable predictions with good accuracy and can be applied to predict shield tunneling parameters under the conditions of composite strata.
李文乾;吴云桓;吴兢业;陈治怀;谢森林;胡安峰
中铁十局集团城市轨道交通集团有限公司,广东广州 511402浙江大学建筑工程学院,浙江杭州 310058浙江大学建筑工程学院,浙江杭州 310058||滨海和城市岩土工程研究中心,浙江杭州 310058
土木建筑
岩土工程多层感知机盾构掘进参数复合地层预测模型K折验证
geotechnical engineeringmulti-layer perceptronshield tunneling parametersmixed groundprediction modelK-fold verification
《深圳大学学报(理工版)》 2024 (001)
50-57 / 8
National Natural Science Foundation of China(51978612,52378419);National College Students'Innovation and Entrepreneurship Training Program(202210335036);Zhejiang Xinmiao Talents Program(2023R401189) 国家自然科学基金资助项目(51978612,52378419);国家级大学生创新创业训练计划资助项目(202210335036);浙江省大学生科技创新活动计划资助项目(2023R40 1189)
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