Department of Electronics, Electrical Engineering and Microelectronics, Silesian University of Technology, 44-100 Gliwice, Poland.
Bombardier Transportation, 40-142 Katowice, Poland.
Sensors (Basel). 2020 May 12;20(10):2754. doi: 10.3390/s20102754.
This paper presents signal filtering methods that can be effectively applied to train detection systems based on the axle counter systems that are currently in operation for train detection and provide information on the unoccupied status of railway tracks and turnouts. Signals from the wheel detectors contain noise, may be impulsive and time-varying, which means that even for the same train, the signals from the following wheels may be different. A problem appears when already homologated hardware (axle counter system) is working in a harsh environment, exposed to disturbances whose parameters significantly exceed standard thresholds. Despite this, the system must continue to provide reliable information. The authors present research on the application of such filters as median, Savitzkey-Golay, and moving average which can be implemented in the equipment currently in use under specific constraints (e.g., limited computational resources). The research results show that appropriately adjusted filters, for example, in terms of type and window size, increase the signal quality and thereby provide reliable information about passing trains, as well as enhance the availability and safety of the axle counter system performance.
本文提出了信号滤波方法，可有效地应用于基于当前运行的用于列车检测的轴计数系统的训练检测系统，并提供有关铁路轨道和道岔空闲状态的信息。轮探测器的信号包含噪声，可能是脉冲和时变的，这意味着即使对于同一列车，后续车轮的信号也可能不同。当已经通过认证的硬件（轴计数系统）在恶劣的环境中工作，并且受到参数明显超过标准阈值的干扰时，就会出现问题。尽管如此，系统仍必须继续提供可靠的信息。作者研究了中值、Savitzkey-Golay 和移动平均等滤波器的应用，这些滤波器可以在特定约束条件下（例如，计算资源有限）在当前使用的设备中实现。研究结果表明，适当调整的滤波器（例如，在类型和窗口大小方面）可以提高信号质量，从而提供有关通过列车的可靠信息，并提高轴计数系统性能的可用性和安全性。
