NASA STI Repository (National Aeronautics and Space Administration) · 2008 · 23 citations · 5 references
Open access
EngineeringSystems EngineeringInternal Combustion EnginesMaintenance EngineeringThermodynamicsCondition MonitoringDamage AssessmentEngine ModelingFailure AnalysisFault DetectionReliability ModelingDamage ModelingEfficiencyEfficiency LossFault PrognosisHealth Index ModelingPerformance DegradationPrognosticsPrognostics And Health Management
This paper describes how damage propagation can be modeled within the modules of aircraft gas turbine engines. To that end, response surfaces of all sensors are generated via a thermo-dynamical simulation model for the engine as a function of variations of flow and efficiency of the modules of interest. An exponential rate of change for flow and efficiency loss was imposed for each data set, starting at a randomly chosen initial deterioration set point. The rate of change of the flow and efficiency denotes an otherwise unspecified fault with increasingly worsening effect. The rates of change of the faults were constrained to an upper threshold but were otherwise chosen randomly. Damage propagation was allowed to continue until a failure criterion was reached. A health index was defined as the minimum of several superimposed operational margins at any given time instant and the failure criterion is reached when health index reaches zero. Output of the model was the time series (cycles) of sensed measurements typically available from aircraft gas turbine engines. The data generated were used as challenge data for the Prognostics and Health Management (PHM) data competition at PHM 08.
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Time series prediction competition: The CATS benchmark
Amaury Lendasse, Erkki Oja, Olli Simula et al. · Neurocomputing · 2007 · 83 citations
Modeling Propagation of Gas Path Damage
Kai Goebel, Hai Qiu, Neil Eklund et al. · 2007 · 22 citations