Transfer learning for bridge monitoring: model testing of four lab-scale multi-span continuous girder bridges under changing temperatures and damage conditions

This dataset is accompanied by a journal paper: “Transfer Learning in Bridge Monitoring: Laboratory Study on Domain Adaptation for Population-Based SHM of Multispan Continuous Girder Bridges”, Valentina Giglioni, Jack Poole, Robin Mills, Ilaria Venanzia, Filippo Ubertini, Keith Worden, MSSP.This dataset was collected with the main aim of investigating methods for population-based SHM. Modal testing was performed on a modular bridge kit which allows for modification of the deck length, and support locations. In this dataset, data are available for four configurations of three span bridges, tested under changing temperatures using an environmental chamber. The bridges were also subjected to several damage conditions. Data were collected via twenty uniaxial 100 mV/g accelerometers, organised in two rows of ten on each edge of the underside of the deck, and the response was measured at a sample rate of 256Hz.

本数据集伴随的学术论文为《桥梁监测中的迁移学习：基于多跨连续梁桥的基于人群的SHM领域自适应实验室研究》，作者为Valentina Giglioni、Jack Poole、Robin Mills、Ilaria Venanzia、Filippo Ubertini、Keith Worden，所属机构为MSSP。该数据集的收集旨在探讨基于人群的SHM（结构健康监测）方法。模态测试在一个可调节桥体长度的模块化桥梁套件上进行，允许调整桥面板的长度和支撑位置。在本数据集中，提供了三个跨桥梁的四种配置数据，这些数据是在环境舱中改变温度条件下进行测试的。桥梁还遭受了多种损伤条件。数据是通过二十个单轴100 mV/g加速度计收集的，这些加速度计被组织成每侧桥面板底部十台一排的两行，响应的测量采样率为256Hz。