Wheel impact load detectors are widespread railway systems used for measuring the wheel–rail contact force. They usually measure the rail strain and convert it to force in order to detect high impact forces and corresponding detrimental wheels. The measured strain signal can also be used to identify the defect type and its severity. The strain sensors have a limited effective zone that leads to partial observation from the wheels. Therefore, wheel impact load detectors exploit multiple sensors to collect samples from different portions of the wheels. The discrete measurement by multiple sensors provides the magnitude of the force; however, it does not provide the much richer variation pattern of the contact force signal. Therefore, this paper proposes a fusion method to associate the collected samples to their positions over the wheel circumferential coordinate. This process reconstructs an informative signal from the discrete samples collected by multiple sensors. To validate the proposed method, the multiple sensors have been simulated by an ad hoc multibody dynamic software (VI-Rail), and the outputs have been fed to the fusion model. The reconstructed signal represents the contact force and consequently the wheel defect. The obtained results demonstrate considerable similarity between the contact force and the reconstructed defect signal that can be used for further defect identification.

中文翻译：

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从多个路边传感器测量的轮轨接触信号重建信息性铁路车轮缺陷信号

车轮冲击载荷检测器是广泛用于测量轮轨接触力的铁路系统。他们通常测量轨道应变并将其转换为力，以检测高冲击力和相应的有害车轮。测得的应变信号还可用于识别缺陷类型及其严重程度。应变传感器具有有限的有效区域，导致从车轮进行部分观察。因此，车轮碰撞载荷检测器利用多个传感器从车轮的不同部分收集样本。多个传感器的离散测量提供了力的大小；然而，它没有提供更丰富的接触力信号变化模式。所以，本文提出了一种融合方法，将收集到的样本与其在车轮圆周坐标上的位置相关联。该过程从多个传感器收集的离散样本中重建信息信号。为了验证所提出的方法，多个传感器已通过临时多体动力学软件 (VI-Rail) 进行仿真，并将输出馈送到融合模型。重建的信号代表接触力，从而代表车轮缺陷。获得的结果表明接触力和重建的缺陷信号之间有相当大的相似性，可用于进一步的缺陷识别。多个传感器已通过临时多体动力学软件 (VI-Rail) 进行模拟，并且输出已输入融合模型。重建的信号代表接触力，从而代表车轮缺陷。获得的结果表明接触力和重建的缺陷信号之间有相当大的相似性，可用于进一步的缺陷识别。多个传感器已通过临时多体动力学软件 (VI-Rail) 进行模拟，并且输出已输入融合模型。重建的信号代表接触力，从而代表车轮缺陷。获得的结果表明接触力和重建的缺陷信号之间有相当大的相似性，可用于进一步的缺陷识别。