Data underlying the publication: A Bidirectional Long Short Term Memory Approach for Infrastructure Health Monitoring Using On-board Vibration Response

The dataset is an Axle-Box Acceleration simulation dataset based on the vehicle-track interaction model developed by Dr. Chen Shen, as described in the following reference. The rail and sleepers are meshed using Timoshenko beam elements, while the ballast and railpads are represented as discrete spring-damper pairs.Clamps and bolts are not explicitly modeled; instead, their stiffness is incorporated into the railpad stiffness, a widely accepted simplification in railway track modeling. The wheel is simplified as a rigid mass, and the wheel-rail contact is modeled using a Hertzian spring. ABA measurements are simulated at an operational speed of 65 km/h by considering floating stiffness reduction. This is the raw dataset and additive white Gaussian noise scenarios are generated as the paper explains. For details on the dataset, please refer to the cited papers.<br>If you use this dataset, ensure proper citation of the following references.<br>*Shen, C., P. Zhang, R. Dollevoet, A. Zoeteman, and Z. Li, Evaluating Railway Track Stiffness Using20 Axle Box Accelerations: A Digital Twin Approach. Mechanical Systems and Signal Processing, vol.21 204, 2023, p. 110730.22<br>*R. R. Samani, A. Nunez, and B. De Schutter. A Bidirectional Long Short Term Memory Approach for Infrastructure Health Monitoring Using On-board Vibration response. Dec. 3, 2024. doi: 10 . 48550 / arXiv.2412.02643. arXiv: 2412.02643 [cs]. Pre-published.

本数据集为基于陈沈博士开发的车轨耦合相互作用模型的轴箱加速度（Axle Box Acceleration, ABA）仿真数据集，相关细节见下述参考文献。钢轨与轨枕采用铁木辛柯（Timoshenko）梁单元进行网格划分，道砟与轨下垫板被建模为离散弹簧-阻尼单元对。扣件与螺栓未进行显式建模，而是将其刚度并入轨下垫板刚度中——这是铁路轨道建模领域被广泛采用的简化方案。车轮被简化为刚性质量块，轮轨接触采用赫兹弹簧（Hertzian spring）模型进行表征。本数据集以65 km/h的运营速度进行仿真，并通过考虑浮动刚度折减来模拟轴箱加速度信号。本数据集为原始数据集，且按照论文所述方法生成了加性高斯白噪声场景。如需了解该数据集的详细信息，请参阅所引用的文献。
若使用本数据集，请务必正确引用下述参考文献。
* Shen, C., P. Zhang, R. Dollevoet, A. Zoeteman, Z. Li. 《利用20个轴箱加速度评估铁路轨道刚度：一种数字孪生方法》，《机械系统与信号处理》，2023年，第21卷第204期，页码110730。
* R. R. Samani, A. Nunez, B. De Schutter. 《基于车载振动响应的基础设施健康监测：双向长短期记忆网络方法》，2024年12月3日。DOI: 10.48550/arXiv.2412.02643，arXiv:2412.02643 [cs]，预印本。