Abstract
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.
Highlights
Train control systems are crucial components to ensure a safe and efficient operation of railways.Researchers try to enhance the reliability of transportation in a variety of manners, namely by constructing a decision support system for railway traffic management [1], or by developing suitable condition monitoring techniques to ensure early, preventive diagnostics for railway systems [2,3].In order to make transportation safe, rail inspections should be done properly
It has to be emphasized that the main goal of the research is application of a different filtration method, which can be implemented inside the “Filters
The expected number of axles (AXL) is described in the tables below, but it is obvious that the decision module (DM) cannot indicate axles for signals A and B
Summary
Train control systems are crucial components to ensure a safe and efficient operation of railways. In order to make transportation safe, rail inspections should be done properly. An efficient crack (broken rail) detection system is proposed by Kumar et al [4] for better diagnostics and inspection. Research is carried out in the direction of using obstacle detections systems (study for image processing presented by Yao and colleagues [5]). Nowadays, such systems are commercially used for monitoring lines (e.g., distributed acoustic sensing based on fiber optic technology) and level crossings (e.g., radars)
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