Abstract. This paper describes a case study of modelbased diagnostics system development for an aircraft Auxiliary Power Unit (APU) turbine system. The offline diagnostics algorithms described in the paper work with historical data of a flight cycle. The diagnostics algorithms use detailed engine systems models and fault model knowledge available to Honeywell as the engine manufacturer. The developed algorithms provide fault condition estimates that allow for consistent detection of incipient performance faults and abnormal conditions.
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