Automated FMEA based diagnostic symptom generation

The comprehensive on-board diagnosis of faults in many aerospace and other engineered systems requires real time execution using limited computational resources, and must also provide verifiable behaviour. This paper shows how a diagnostic system satisfying these requirements can be automatically generated from the model based simulation used to produce an automated Failure Modes and Effect Analysis (FMEA). The resulting diagnostic system comprises a set of efficiently evaluated symptoms and their associated faults. The symptoms are complete in that they include all necessary observations required to determine applicable system operating states, unlike other work that finesses this problem by having models for each operating state and producing diagnostics for each operating state separately. The symptoms are also efficient because they abstract complex system behaviour based on observations available to the diagnostic system and only preserve sufficient symptom detail to isolate faults given these available observations. This work has been done in the context of diagnosing autonomous aircraft, and is illustrated with examples from that domain. The models used as a basis for automated generation of diagnostics were originally produced to automate the production of a FMEA report, and the paper also considers the relationship between FMEA and diagnostics that provides verification of the failure effects predicted by the simulation and hence validation of the generated symptoms.