Development and Implementation of a <u>F</u>ramework for <u>A</u>erospace <u>Ve</u>hicle <u>R</u>easoning (FAVER)

This paper discusses the development and implementation of architecture a Framework for Aerospace Vehicle Reasoning, `FAVER'. Integrated Health Management systems require holistic view aircraft to isolate faults cascading between systems. FAVER is system-agnostic framework developed such propagating by incorporating Digital Twins (DTs) reasoning techniques. The flexibility work with different types scales DTs diagnostics, its ability adapt expand previously unknown new are demonstrated in this paper. also shows novel combination relationship matrix fault attributes database used structure knowledge FAVER's expert system. provides working mechanism at system level, identify their root causes, predict effects vehicle level. Four demonstration purposes: i) Electrical Power System, ii) Fuel iii) Engine, iv) Environmental Control use case scenarios adapted from real incidents. pros cons via demonstrations evaluates performance through comparative study supervised neural network model.