Design And Implementation Of Data Warehouse For High Speed Railway Catenary

Indubitably,China's high-speed railway has developed rapidly during the last decade.The popularization of high-speed railway is of great significance to national economic development and people's travel experience.High-speed railway catenary,an indispensable part of traction power supply system,is the only power supply channel for high-speed train,and its good operation status plays an important role in ensuring the safety and reliability of high-speed railway.A large number of business data have been generated and accumulated during the operation of high-speed railway catenary.The data truly reflects the operation status of high-speed railway catenary.It will be of great significance for excavating useful information that can support the operation and maintenance decision-making of high-speed railway catenary through comprehensive analysis and utilization of these data.However,the catenary data of high-speed railway has many characteristics,such as various kinds,decentralized storage,different structures and non-standard,which may cause many inconveniences and difficulties for the comprehensive analysis and utilization of data.Therefore,this paper uses the theory and technology of data warehouse to study the construction of high-speed railway catenary data warehouse.By integrating multi-source heterogeneous data of high-speed railway catenary,it provides a unified,regularized and standard data environment for the comprehensive analysis and utilization of data.The main work of this paper includes:Firstly,this paper studies the business processes of high-speed rail catenary in China,and fully understands the business data generated by the business processes,including the types,sources,meanings and characteristics of the data.Furthermore,this paper analyzes the problems existing in the process of recording,storage,management and utilization of the original data,and clarifies the construction requirements of high-speed railway catenary data warehouse.Secondly,the data model of high-speed railway catenary data warehouse is designed by following the method of Kimball dimension modeling,which is developed progressively in three levels:conceptual model,logical model and physical model.The conceptual modeling determines three themes of high-speed railway catenary data warehouse,namely intrinsic parameter theme,detection parameter theme and defect theme,and analyses the facts and dimensions that each theme should contain.The logical modeling defines the attributes that fact tables and dimension tables should contain,as well as the primary and foreign key relationships between fact tables and dimension tables.The physical modeling defines physical storage information of fact table and dimension table according to Oracle database management system,including field name,data type,constraint,etc.Then,according to the characteristics of high-speed railway catenary data source and the data model of target data warehouse,the extract-transform-load(ETL)process of high-speed railway catenary data is designed.Data extraction is done online and incrementally,and is executed regularly by automatic dispatching program.The extracted raw data is stored in the operational data storage area.Data cleaning checks the extracted data according to the inspection rules and removes the unqualified data.Data transformation converts the cleaned data into unified data format according to the coding rules.Data loading loads dimension data and fact data into dimension table and fact table of data warehouse respectively.Finally,based on the above design of ETL process,the ETL process of the catenary defect original data collected on site is realized by using data integration tool Kettle,which includes four parts:data extraction,data cleaning,data conversion and data loading.After successful loading,the high-speed railway catenary data warehouse is created.Through Navicat for Oracle's custom query and report making function,the access and application of high-speed rail catenary data warehouse are demonstrated.