Fault Data Analysis And Software Design Of A Bullet Train Segment Based On Big Data

China’s railway development has entered the high-speed era,the demand for EMU is increasing day by day.Along with our country of the emu’s increasing,the emu in the operating maintenance failure data accumulated more and more,to establish the emu failure data management platform was carried out on the failure data collection,we analyzed the emu regularity,which can take corresponding measures,the optimization of emu maintenance process.In this paper,a dynamic vehicle failure data section as the research object,the theory of reliability engineering is presented,the emu fault data inductive analysis model is established,set up based on B/S system of the emu failure data processing platform,and bogie failure data of a word association rules and clustering analysis,finally combining the regularity of bogie maintenance Suggestions are put forward.The main research contents of this paper are as follows:(1)Study reliability theory and three reliability analysis methods,FMECA,FMEA and FTA,and study their relationship.And the implementation process of association rules and coword clustering analysis is briefly summarized.(2)A induction and analysis model of EMU fault data is built.Firstly,the definition,classification and source of EMU fault are simply introduced.Combined with the actual situation FMEA analysis table of EMU fault,the induction and analysis model of EMU fault data is built.(3)A fault data processing platform for EMU based on B/S system was built,and the fault data collected by the fault data processing platform was statistically analyzed.Finally,the bogie part with the largest fault data proportion was selected for Apriori association rule analysis and coword cluster analysis,and the fault rule was obtained.