A Method for Fault Diagnosis of Aviation Engine Gas System

Gas system is the key system of aero-engine. Because of its harsh working environment, it is difficult to diagnose it effectively. For this reason, this paper researches and proposes a method of aero-engine gas system fault diagnosis based on WOA-SVM. The problems of long optimization time of genetic algorithm and early convergence of particle swarm are overcome. Six parameters, T2, T25, T6, N2c25, Alfa2, and N1 of the pneumatic system are selected. First, the WOA algorithm is used to optimize the relevant parameters of the SVM to obtain the best optimized parameters. Secondly, based on the obtained optimal optimization parameters of the SVM, a fault diagnosis model of the gas system is created, and the fault of the aero-engine gas system is studied by using the created SVM model with the best optimized parameters. Finally, the correctness of the created fault diagnosis model was verified by simulation tests. The result shows that the fault diagnosis method of aero-engine gas system based on WOA-SVM can achieve the fault diagnosis of aero-engine gas system greatly. The fault diagnosis accuracy rate is significantly higher than the traditional optimization algorithm, which has a good application prospect.