2008 · 1.6K citations · 14 references
EngineeringMechanical EngineeringSystems EngineeringInternal Combustion EnginesMaintenance EngineeringThermodynamicsCondition MonitoringDamage AssessmentEngine ModelingFailure AnalysisFault DetectionReliability ModelingDamage SimulationEfficiencyEfficiency LossFailure SimulationHealth Index ModelingModel SimulationPerformance DegradationPerformance Degradation Modeling
The flow and efficiency degradation represents an unspecified fault that progressively worsens. The study aims to model damage propagation within aircraft gas turbine engine modules. Using a thermo‑dynamical simulation, sensor response surfaces are generated as functions of flow and efficiency variations, random exponential deterioration is imposed, and damage is propagated until a health‑index‑based failure criterion is met. The model produces cycle‑based time series of sensor measurements, which were used as challenge data for the PHMpsila08 prognostics competition.
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 PHMpsila08.
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Metrics for evaluating performance of prognostic techniques
Abhinav Saxena, José Celaya, Edward Balaban et al. · 2008 · 502 citations
Standardizing the Performance Evaluation of Short-Term Wind Power Prediction Models
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