A kind of approach for aero engine gas path fault diagnosis

摘要

Support vector machine (SVM) has good generalization performance and is suitable for solving small sample classification problems, so it is often used in the fault diagnosis for aero engine gas path. In this paper, the traditional genetic algorithm and the idea of simulated annealing are combined to optimize the parameters of SVM, and a fault diagnosis method of aero engine gas path based on parameter optimized support vector machine is presented. This method is used to diagnose the aero engine gas path fault to verify the feasibility and effectiveness. The experimental results show that the algorithm can effectively select the parameters of SVM, and ensure the accuracy of fault diagnosis.