Research On RDC Data Generation And Validation Method Of CTCS-1 Train Control System

Chinese Train Control System(CTCS)is a safety critical system used to ensure train operation safety and efficiency.As the carrier of signalling equipment information,train status information and line information,the correctness of train control data is an important prerequisite for the safe operation of trains.Currently,for different train control subsystems,the train control data is described in different ways and there is no specific data specification.The validation of train control data mainly relies on the combination of manual work and simulation test,which is inefficient and unable to guarantee data correctness.In view of the above issues,taking the static data validation of Regional Data Center(RDC)which is the core equipment of CTCS-1 train control system as an example,focusing on studying the RDC data organization design and data validation,this thesis firstly establishes the model of RDC static data,then proposes the overall framework of data validation process,and finally designs and develops the RDC data automation validation software to realize the automatic validation of RDC static data.The works completed by the thesis include:(1)The RDC data organization method was studied and the RDC static data model was established.By analyzing the RDC system requirements,the RDC static data was classified into point elements,track elements and regional elements,and the logical relationship model between data elements was constructed,which could not only reflected the track topology relationship but also facilitated later maintenance and update.Finally,the RDC static data structure model was built up,which was then combined with the track data to generate the RDC static database.(2)The overall framework of data modeling and validation was proposed,which included four stages,namely extraction of data constraint rules,establishment of data validation model,checking of data validation model,and implementation of data validation software.Firstly,according to the train control data specification and RDC functional requirements,and with reference of data preparation and validation experiences,the data constraint rules were summed up into domain value relation rules,mapping relation rules,association relation rules and continuity relation rules.In order to ensure the comprehensiveness and systematicness of the validation process,a method combining horizontal validation and vertical validation was proposed for the validation of data fields,and the CSP model for data validation process was established based on data constraint rules.(3)Based on the above formal data validation model,a two-way tracking chain between data constraint rules,data validation model,model checking and result analysis,was established and the RDC data validation model conforming to the data constraint rules was obtained.The model was tested from three aspects:correctness,validity and safety.Firstly,the ProB verifier was used to verify whether the model had deadlock,livelock and other issues and whether the constraint rules were satisfied.Secondly,through CSP-Petri model transformation,the safety of the model was analyzed by means of Petri net reachable tree analysis.Finally,through multiple model modification and retest,the model was proved to satisfy the data validation requirement.(4)Based on the above data validation model,the RDC data automation validation software was designed and implemented with.NET Framework platform.By comparing the actual track data which were validated by the software and the manual data validation methods,the result showed that the validation of RDC data by the automated validation software could improve the validation efficiency and ensured the correctness of the data,which also proved the feasibility of the RDC data validation method.