Sensor Fault Diagnosis of Aero Engine Control System Based on Honey Badger Optimizer

Traditional redundancy detection methods are challenging to achieve fault detection due to high modeling complexity. Aiming at this problem, a data-driven engine sensor fault diagnosis method based on data is established. This paper proposes an intelligent fault diagnosis method based on meta-heuristic optimization, which uses honey badger optimization for feature selection to reduce redundancy information and improve classification accuracy in the problem of aero-engine sensor fault diagnosis. The accuracy of the proposed algorithm is significantly better than the traditional method.