Research on an Intelligent Fault Diagnosis System for Aircraft On-Board Equipment Based on Digital Twin Technology

We propose an intelligent fault diagnosis method for aircraft on-board equipment. It utilizes the simulated fault data generated by a digital twin model to supplement the limited available actual fault data, establishing a library of effective fault diagnosis algorithms through algorithmic model training. Subsequently, an intelligent fault diagnosis system is developed, capable of diagnosing faults in aircraft airborne equipment. This method supports the aircraft maintenance personnel to formulate repair and maintenance strategy of airborne equipment, offering a significant engineering application.