Research On Fault Diagnosis Of TT&C Equipment Based On Complex Network Theory

With the rapid development of the aerospace industry in China,as the main part of aerospace TT&C(Telemetry,Track and Command)system,the use of the TT&C equipment will be more frequent.The cross penetration of various disciplines and technologies in the equipment makes the equipment more and more complicated,and the probability of failure increases accordingly.The impact on the TT&C task is self-evident.Therefore,rapid and accurate fault diagnosis of equipment is an urgent problem to be solved.Complex networks is a research hotspot in recent years,with the deepening of its theoretical and applied research,people began to use this method to study the real world in some large,complex systems,the TT&C equipment is one of them.As an important part of the TT&C equipment,the antenna servo feed subsystem has complex structure and high probability of failure.So the system is the focus of the study.In this paper,a fault diagnosis method based on complex network is proposed,and a network model is established by using the fault data samples of the antenna servo feed subsystem and the characteristics of the complex network community structure.Aiming at the characteristics of antenna servo feed subsystem with many types of equipment and different sensor data types,this paper studies the distance between nodes of complex network and proposes to use standard Euclidean distance instead of traditional Euclidean distance.Through algorithm demonstration and practical verification,the problem of data correlation between different data types is well solved,so as to solve the problem of edge weight of complex network based on different data types.The complex network and clustering method are combined to present a clustering method model based on Newman's fast algorithm.Newman's fast algorithm is used for hierarchical clustering of fault samples from the bottom up.Based on the analysis of fault data of the antenna servo feed subsystem,it is concluded that this algorithm is suitable for fault diagnosis of the antenna servo feed subsystem.