Study On The Propagation Characteristics Of Aero-engine Fault Based On Complex Network

Aero engine is an important part of aerospace equipment, in the vast majority of cases are in the safety threshold with a certain degree of fault, and due to the complexity of its internal structure and any parts of a fault with in the unit spread, diffusion, accumulation and magnification ability, which leads to more serious problems, as can master fault propagation between component parts, we can take preventive measures. Aero engine within the complex components of intertwined to form a complex network, using the theory and method of complex network analysis of aero-engine components of fault propagation characteristics, find the highest risk of fault propagation path and locate the fault source, as well as the fault types of components for the diagnosis of aviation engine, to provide reference and basis for the optimization of maintenance, operation, to ensure the safety and reliability of aero engine operation, it has great significance.The main research work of this paper includes the following aspects:1) Basic structure and typical fault analysis of aero engine. this paper analysis on a certain type of aero engine components and their coupling relationship, the internal structure and parts of the typical failure mechanism are introduced in detail; To provide basis for the study of the fault propagation characteristics of the following aviation engine.2) The highest risk path analysis of aero engine fault based on small world network model. According to the physics of aero engine, setting reasonable assumptions, and abstract build the topological structure of fault model, and validation the small world characteristic through the analysis of the network characteristic parameters of model. Combining small world network features of model and the principle of step k fault spread, determining the weights of edges between the nodes in the network, to build mathematical model by the objective function which is the sum of spread path fault transmission intensity for solving the highest risk paths, and solving the highest risk path of aero engine fault, providing reference and basis for aero engine fault prevention.3) Aero engine fault source localization based on Petri net. Based on level of aircraft engine structure, combining with the highest risk of failure in the process of the path analysis of key parts, to prevent the construction of a fault to prevent parts such as the rotor system fault diagnosis tree, the fault diagnosis tree as the construction of the intermediate state to realize fault petri net model, through the fault of petri net source of positive and reverse reasoning to calculate the maximum probability of failure, then provide reference and basis for aero engine fault fast positioning.4) Diagnosis of aeroengine components fault type based on clustering optimized fusion. Put forward a fusion method of clustering analysis which is aimed to the support bearing fault type diagnosis of aero engine components. First, taking a variety of clustering analysis method to diagnose fault data, respectively, to get the initial clustering fusion weight matrix, and then uses genetic algorithm to optimize weight matrix and get the final fusion diagnosis decision to get the final diagnosis, which the accuracy and reliability are improved than a single cluster diagnosis.