{"title":"基于贝叶斯方法的铁路自动化系统诊断","authors":"W. Nowakowski, P. Bojarczak, Z. Łukasik","doi":"10.1109/ICRIEECE44171.2018.9008871","DOIUrl":null,"url":null,"abstract":"The basic function of railway automation systems is allowing a safe and fluent railway traffic control. Along with the technical progress these systems are constantly being improved. The process of their development at the moment is influenced by the modern information technology, that is why the contemporary railway automation systems are computer systems. They allow a remote control of the railway traffic on many train service stations from one place, which is Operation Control Centre (OCC). This subject is also related to the centralization of the railway automation systems technical diagnosis in Maintenance and Diagnostics Centres (MDC). Despite the constant technical progress, there are no standards concerning the way and range of gathering diagnostic data and the method of its analysis. The authors of the article have noticed this important issue and have decided to make an attempt to formulate and develop a method of railway automation systems diagnosis. The method proposed in the article can be counted as logic diagnosis and one of the Bayesian methods. A verification of the method has been performed on the example of a Level Crossing Protection System (LCPS). The obtained positive effects are an encouragement for further research and consideration of other types of railway automation systems.","PeriodicalId":393891,"journal":{"name":"2018 International Conference on Recent Innovations in Electrical, Electronics & Communication Engineering (ICRIEECE)","volume":"79 ","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2018-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Railway automation systems diagnosis based on Bayesian method\",\"authors\":\"W. Nowakowski, P. Bojarczak, Z. Łukasik\",\"doi\":\"10.1109/ICRIEECE44171.2018.9008871\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The basic function of railway automation systems is allowing a safe and fluent railway traffic control. Along with the technical progress these systems are constantly being improved. The process of their development at the moment is influenced by the modern information technology, that is why the contemporary railway automation systems are computer systems. They allow a remote control of the railway traffic on many train service stations from one place, which is Operation Control Centre (OCC). This subject is also related to the centralization of the railway automation systems technical diagnosis in Maintenance and Diagnostics Centres (MDC). Despite the constant technical progress, there are no standards concerning the way and range of gathering diagnostic data and the method of its analysis. The authors of the article have noticed this important issue and have decided to make an attempt to formulate and develop a method of railway automation systems diagnosis. The method proposed in the article can be counted as logic diagnosis and one of the Bayesian methods. A verification of the method has been performed on the example of a Level Crossing Protection System (LCPS). The obtained positive effects are an encouragement for further research and consideration of other types of railway automation systems.\",\"PeriodicalId\":393891,\"journal\":{\"name\":\"2018 International Conference on Recent Innovations in Electrical, Electronics & Communication Engineering (ICRIEECE)\",\"volume\":\"79 \",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2018-07-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2018 International Conference on Recent Innovations in Electrical, Electronics & Communication Engineering (ICRIEECE)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICRIEECE44171.2018.9008871\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2018 International Conference on Recent Innovations in Electrical, Electronics & Communication Engineering (ICRIEECE)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICRIEECE44171.2018.9008871","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Railway automation systems diagnosis based on Bayesian method
The basic function of railway automation systems is allowing a safe and fluent railway traffic control. Along with the technical progress these systems are constantly being improved. The process of their development at the moment is influenced by the modern information technology, that is why the contemporary railway automation systems are computer systems. They allow a remote control of the railway traffic on many train service stations from one place, which is Operation Control Centre (OCC). This subject is also related to the centralization of the railway automation systems technical diagnosis in Maintenance and Diagnostics Centres (MDC). Despite the constant technical progress, there are no standards concerning the way and range of gathering diagnostic data and the method of its analysis. The authors of the article have noticed this important issue and have decided to make an attempt to formulate and develop a method of railway automation systems diagnosis. The method proposed in the article can be counted as logic diagnosis and one of the Bayesian methods. A verification of the method has been performed on the example of a Level Crossing Protection System (LCPS). The obtained positive effects are an encouragement for further research and consideration of other types of railway automation systems.