Abstract
The railway traffic control systems’ development arise from the need to ensure, by these systems, a high level of safety and reliability, and a required functionality. It is linked with the use of technical achievements in constructing new devices and systems. This means that contemporary railway traffic control systems are computer systems, using modern ICT systems. Thanks to this fact, new possibilities for the diagnosis of these systems arise, as well as maintenance and diagnostics centres are created. At the moment, there are no standards regarding the way and range of collecting diagnostic data. That is why, the authors of the paper have proposed a method for diagnostic data collection, consisting in using SNMP, which is commonly used in the diagnosis of computer networks. The research has been conducted for one of the railway traffic control systems – the Axle Counting Systems (ACS). Therefore, two MIB bases, in which diagnostic data structure was defined, have been developed, as well as software of the SNMP agent and manager has been worked out. The SNMP agent allows modification of data concerning the axle counting system and it makes the data available to the SNMP manager. It also has an implemented function to notify the manager about faults in the form of sent traps. The conducted experimental research has proven usefulness of this technology, and, at the same time, the need to extend the research to include other types of the railway traffic control systems.
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This material is based upon work supported by National Centre for Research and Development under Grant No. PBS3/A6/29/2015 entitled “The system for maintenance data acquisition and analysis of reliability and safety of traffic control systems”.
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Nowakowski, W., Bojarczak, P., Łukasik, Z. (2018). A Diagnostic Method for Axle Counting Systems Based on the SNMP Protocol. In: Kováčiková, T., Buzna, Ľ., Pourhashem, G., Lugano, G., Cornet, Y., Lugano, N. (eds) Intelligent Transport Systems – From Research and Development to the Market Uptake. INTSYS 2017. Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering, vol 222. Springer, Cham. https://doi.org/10.1007/978-3-319-93710-6_6
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