Agent based heterogeneous data integration and maintenance decision support for high-speed railway signal system

In this paper, we propose a novel framework of integration of multi-source heterogeneous data and intelligent maintenance decision support for High-speed Railway Signal System. The framework uses the multi-agent system to deal with the multi-source data. Each agent has its own task varying from transferring RDB (Rational Database) data to RDF (Resource Description Framework) file, and then fusing local RDF to global RDF by Apache Jena API and D2RQ. In addition, a CBR (Case-Based Reasoning) based intelligent maintenance decision support for the fault diagnosis has been constructed by combing the rough set with the Euclidean distance. The correctness and efficiency of the proposed framework has been verified by maintenance data derived from VOBE (Vehicle Equipment On Board) of CTCS-300T operating on Wuhan-Guangzhou Line.