Research3h ago
LLM Enhances Aviation Fault Diagnosis Framework
A new framework uses JSBSim to generate 23-channel engine health data for general aviation aircraft. It integrates a multi-fidelity digital twin with FMEA knowledge to overcome scarce real-world fault data. An LLM then converts these residual features into interpretable diagnostic reports. This approach provides a scalable way to train fault detection systems without risking physical airframes.