基于加载力和多位移的无砟轨道分层刚度检测

IF 5.6 1区工程技术 Q1 ENGINEERING, CIVIL

Engineering Structures Pub Date : 2024-10-29 DOI:10.1016/j.engstruct.2024.119230

Shuaijie Miao , Liang Gao , Tao Xin , Hui Yin , Yonggui Huang , Hong Xiao , Xiaopei Cai

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引用次数: 0

摘要

掌握轨道刚度状况对铁路维护意义重大。然而，关于无砟轨道分层刚度的数据采集和检测方法的研究却十分匮乏，且极具挑战性。本文提出了一种基于加载力和多位移的分层刚度检测数据采集策略。该数据集由沿铁路线采集的加载力和多个位移组成，能有效反映轨道分层刚度，包括整体轨道刚度和板上板下刚度。将刚度检测数据输入经粒子群优化（PSO-BP）的 BP 模型，挖掘不同分层缺陷与轨道分层刚度波动之间的相关性，进而预测轨道分层刚度序列并定位局部异常。在此基础上，构建了一个包含 25 个异常分层刚度案例的图像数据集，这些案例由不同程度的异常紧固件刚度、砂浆空隙、基层沉降及其重叠引起。通过迁移学习预训练的 Resnnet18 模型用于识别图像数据集中的分层刚度异常情况，准确率为 94.63%。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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Layered stiffness detection of ballastless track based on loading force and multiple displacements

Grasping the track stiffness status is significant to railway maintenance. However, the research on the data collection and detection method of ballastless track layered stiffness is lacking and challenging. This article proposes a data collection strategy for layered stiffness detection based on loading force and multiple displacements. The dataset, which consists of loading force and multiple displacements collected along the railway line, effectively reflects track layered stiffness, including the overall track stiffness and the slab upper and bottom stiffness. The stiffness detection data is input into the BP model optimized by particle swarm optimization (PSO-BP) to mine the correlation between different sublayer defects, track layered stiffness' fluctuation, and then predict the layered stiffness sequences and locate local anomalies. On this basis, an image dataset of 25 abnormal layered stiffness cases is constructed, caused by different degrees of abnormal fastener stiffness, mortar void, subgrade settlement and their overlap. The Resnnet18 model, pre-trained by transfer learning, is used to identify layered stiffness anomaly cases in image datasets, and the accuracy is 94.63 %.

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来源期刊

Engineering Structures 工程技术-工程：土木

CiteScore

10.20

自引率

14.50%

发文量

1385

审稿时长

67 days

期刊介绍： Engineering Structures provides a forum for a broad blend of scientific and technical papers to reflect the evolving needs of the structural engineering and structural mechanics communities. Particularly welcome are contributions dealing with applications of structural engineering and mechanics principles in all areas of technology. The journal aspires to a broad and integrated coverage of the effects of dynamic loadings and of the modelling techniques whereby the structural response to these loadings may be computed. The scope of Engineering Structures encompasses, but is not restricted to, the following areas: infrastructure engineering; earthquake engineering; structure-fluid-soil interaction; wind engineering; fire engineering; blast engineering; structural reliability/stability; life assessment/integrity; structural health monitoring; multi-hazard engineering; structural dynamics; optimization; expert systems; experimental modelling; performance-based design; multiscale analysis; value engineering. Topics of interest include: tall buildings; innovative structures; environmentally responsive structures; bridges; stadiums; commercial and public buildings; transmission towers; television and telecommunication masts; foldable structures; cooling towers; plates and shells; suspension structures; protective structures; smart structures; nuclear reactors; dams; pressure vessels; pipelines; tunnels. Engineering Structures also publishes review articles, short communications and discussions, book reviews, and a diary on international events related to any aspect of structural engineering.