Department of Structural Engineering, Norwegian University of Science and Technology (NTNU), 7491 Trondheim, Norway.
Sensors (Basel). 2022 Feb 24;22(5):1772. doi: 10.3390/s22051772.
This paper presents a methodology for classifying train passages into different types with a weigh-in-motion (WIM) system to allow the calibration of railway fatigue load models and identify individual vehicles from the measurements for the continuous calibration of railway WIM stations from in-service trains. The quality assurance of the measured responses is demonstrated using statistical methods. This paper discusses the measurement station, the method used for processing the raw data, the algorithm used to identify the train types and vehicles automatically, and the limits of the obtained load spectra. The measurement errors are demonstrated to be satisfying for use in fatigue load model calibration. Furthermore, this paper proposes actions for accurately obtaining the actual traffic conditions and describes the future work required in this area.
本文提出了一种利用称重式动态检测系统（WIM）将列车通道分类为不同类型的方法，以便对铁路疲劳载荷模型进行校准，并从测量中识别出个别车辆，从而对铁路 WIM 站进行连续校准。利用统计方法验证了测量结果的质量保证。本文讨论了测量站、用于处理原始数据的方法、用于自动识别列车类型和车辆的算法，以及获得的载荷谱的限制。测量误差足以用于疲劳载荷模型校准。此外，本文提出了准确获取实际交通状况的措施，并描述了该领域未来需要的工作。
