| In the traditional civil aviation transportation industry,the airline acquires aircraft operation data with limited means,lacks model algorithms that match the health state,lacks analysis of failure modes and impacts of aircraft critical systems,and application of fault solving methods.It is impossible to fully grasp the health state of the aircraft and predict the health status of the aircraft.This paper studies civil aircraft fault diagnosis and health management service technologies based on big data,which can prevent aircraft anomalies and improve the ability to solve aviation safety problems.The specific details are as follows:(1)Analyze the commercial aircraft fault diagnosis and safety forecast business requirements.Firstly,the analysis of civil aircraft fault diagnosis and safety forecast business involves the value of relevant stakeholders and related stakeholders.Then through the analysis of business processes and the input and output data involved in them,the current civil aircraft fault diagnosis and health management problems are summarized.Finally put forward the functional requirements and data requirements.(2)Propose the architecture of fault diagnosis and safety forecast platform based on big data.Build platform logic structure,service mode,function module and physical layout,and map big data technology to fault diagnosis and health management business to get big-data-based fault diagnosis and health management business content.(3)Propose an improved prediction model for flight safety based on ARIMA-SPA and civilian aircraft fault diagnosis technology based on improved FMEA to improve fault diagnosis and forecast accuracy and efficiency.(4)Set up a prototype system for civil aircraft fault diagnosis and health management big data analysis,including the development architecture,development environment,and tools of the prototype system.Based on the previous study,the system function was verified. |
