Health classification of hydraulic system based on k-means

Abstract

Up to now, there is still a lack of systematic and in-depth research on the failure regularity and reliability of aircraft hydraulic system and its accessories. The main reason is that this kind of research can not only have disadvantages of low degree of informatization, standardization, automation and intelligence, but also has the difficulty of statistical analysis of data. Although aircraft hydraulic system using fault data is relatively scarce, flight parameters data is relatively abundant and easy to obtain. Based on the analysis of the main failure modes of hydraulic system and the selection of health status characterization parameters, the flight parameter data are processed, and the maintenance records are combined to evaluate and predict the health status of the system and diagnose the faults, so as to help improve the economy of maintenance and support and realize predictive maintenance. The flight parameters generated during the flight and maintenance of the aircraft contain the health status information and performance change trend of the airborne system. Through the analysis and processing of flight parameter data, the airborne system health monitoring can not only provide reference for the maintenance decision, but also help to promote the "situational maintenance" and improve the safety and reliability of flight.