Feed-Forward Neural Network for health monitoring of a parallel hybrid electric power system

Abstract Hybrid engines are becoming more and widespread. Electric energy instead is a valid help to reduce the environmental impact. In hybrid engines, number of components higher this results in decrease reliability. With Engine Health Monitoring (EHM) we mean set techniques used monitor health status system based on values assumed by some related parameters. Artificial Intelligence (AI) methods widely nowadays discipline. paper, an EHM approach was developed constituting turboshaft. The dynamic model electric power described accompanying paper. Feed-Forward Neural Network (FFNN) as AI tool built just cited system. engine modelled with Simulink, perform series steady-state simulations implementing degradation condition selected components. simulated changing value Performance Parameters (PPs) each simulation were obtain dataset useful train FFNN predict same PPs degraded case.