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随机车流荷载下基于正则化的位移影响线识别方法研究

孙畅 昝建航 李斌 黄民水

武汉工程大学学报2025,Vol.47Issue(2):224-230,7.
武汉工程大学学报2025,Vol.47Issue(2):224-230,7.DOI:10.19843/j.cnki.CN42-1779/TQ.202405001

随机车流荷载下基于正则化的位移影响线识别方法研究

Regularization-based identification method for displacement influence lines under random traffic loads

孙畅 1昝建航 1李斌 2黄民水1

作者信息

  • 1. 武汉工程大学土木工程与建筑学院,湖北 武汉 430074||绿色土木工程材料与结构湖北省工程研究中心,湖北 武汉 430074
  • 2. 广西壮族自治区贵港市公路发展中心,广西 贵港,537100
  • 折叠

摘要

Abstract

To fit the actual traffic conditions of bridge in operation,considering the randomness of traffic flow crossing the bridge,a method was proposed to identify the influence line of a simply supported beam bridge under random traffic loads.By establishing a model for random traffic loads and collecting bridge response data under such conditions,a mathematical model for influence line identification was developed based on traffic parameters.This model transforms random traffic loads into axle response superposition and utilizes a sparse regularization method to identify the bridge influence line.Using a numerical model of a 20 m simply supported beam bridge,midspan displacement responses under four different vehicle speeds and random traffic loads were extracted.Employing empirical mode decomposition to remove vehicle dynamic response and regularization to extract the bridge influence line,the feasibility and effectiveness of the method were confirmed.The identification effects were quantitatively evaluated by using global error and peak relative error.Results demonstrated that the proposed method effectively eliminates dynamic fluctuations due to vehicle loads,accurately identifies the displacement influence line of simply supported beam bridges under both single vehicle and random traffic load scenarios,and exhibits high recognition accuracy.Notably,the largest identification error occurred when a single vehicle travelled at a speed of 72 km/h,with global and peak relative errors of 4.959%and 9.897%respectively.Under random traffic load conditions,the global error in identifying the influence line was 4.53%,with a peak relative error of 7.89%.

关键词

随机车流/影响线识别/车致响应/稀疏正则化

Key words

random traffic load/influence line identification/vehicle-induced response/sparse regularization

分类

交通运输

引用本文复制引用

孙畅,昝建航,李斌,黄民水..随机车流荷载下基于正则化的位移影响线识别方法研究[J].武汉工程大学学报,2025,47(2):224-230,7.

基金项目

贵港市自筹经费科研项目(贵路养函[2023]40号) (贵路养函[2023]40号)

武汉工程大学学报

1674-2869

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