Vision-based multi-target monitoring systems for bridge structures provide a comprehensive evaluation of structural safety. However, their application to field bridges has been constrained by challenges such as the trade-off between the field of view (FOV) and accuracy, as well as the impact of camera orientation and complex backgrounds on measurement effectiveness. This study introduces a robust monocular vision-based monitoring system (RMVMS) for multi-target displacement measurement. First, a system configuration determination method is developed to achieve an effective balance between FOV and accuracy. Next, a hybrid network structure, ConvTransNet, is introduced to mitigate the impact of complex background disturbance. Additionally, a novel multi-target displacement transformation model (MDTM) is proposed to correct errors arising from camera orientation. Moreover, a boundary loss function and an RMSProp learning rate schedule were implemented during training, enabling ConvTransNet to achieve optimal performance with a P-R threshold of 0.45. A 4-meter laboratory-scale bridge model test demonstrated the superiority of ConvTransNet over existing segmentation models on a custom dataset formatted according to Pascal VOC 2012 standards. MDTM effectively reduced orientation-induced errors from 17.93 % to 1.53 %. The efficiency and robustness of RMVMS were further validated on a tied arch bridge, achieving RMSE and NRMSE below 0.162 mm and 3.63 %, respectively, confirming its capability for precise multi-target displacement monitoring in field applications.

中文翻译：

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强大的基于单目视觉的监测系统，用于复杂背景下桥梁的多目标位移测量


基于视觉的桥梁结构多目标监控系统提供了对结构安全性的全面评估。然而，它们在场桥上的应用受到挑战的限制，例如视场 （FOV） 和精度之间的权衡，以及相机方向和复杂背景对测量效果的影响。本研究介绍了一种用于多目标位移测量的稳健的基于单目视觉的监测系统 （RMVMS）。首先，开发了一种系统配置确定方法，以实现 FOV 和精度之间的有效平衡。接下来，引入一种混合网络结构 ConvTransNet 来减轻复杂背景干扰的影响。此外，提出了一种新的多目标位移变换模型 （MDTM） 来纠正相机方向引起的误差。此外，在训练过程中实现了边界损失函数和 RMSProp 学习率计划，使 ConvTransNet 能够以 0.45 的 P-R 阈值实现最佳性能。一项 4 米实验室规模的桥梁模型测试在根据 Pascal VOC 2012 标准格式化的自定义数据集上证明了 ConvTransNet 优于现有分割模型。MDTM 有效地将取向诱导的误差从 17.93 % 降低到 1.53 %。RMVMS 的效率和稳健性在系杆拱桥上进一步验证，RMSE 和 NRMSE 分别低于 0.162 mm 和 3.63%，证实了其在现场应用中精确监测多目标位移的能力。