Journal of Engineering for Gas Turbines and Power · 1992 · 49 citations · 0 references
Fault DiagnosisEngineeringMeasurementIndustrial EngineeringDiagnosisFault ForecastingIntelligent SystemsSystem DiagnosisCondition MonitoringReliability EngineeringData ScienceSystems EngineeringStatisticsReliabilityOptimal MeasurementHealth Estimation ParametersStructural Health MonitoringComputer EngineeringMonitoring SystemAdaptive Performance ModelingFault EstimationHealth Index SelectionProcess ControlSensor HealthIndustrial InformaticsFault DetectionGas Turbine EngineHealth Informatics
In this paper, we present a method for defining the health estimation parameters and the measurements that must be used when a monitoring system for an engine is being set up. The particular engine layout, the available measuring instruments, and the accuracy by which data can be collected are the factors taken into account. The particular health condition estimation factors that have to be used are defined as a function of this information and the desired depth of fault identification. A fast selection procedure based on the method of singular value decomposition is presented. The uncertainty in the estimations is also derived, thus giving an additional element of information useful for decision making. The proposed method, together with adaptive performance modeling, provides a self-sufficient tool, which can be applied for setting up and subsequent exploitation of a health monitoring expert system. The advantage of the procedure is that it provides a frame of application, allowing quick implementation in a new engine of interest, other than the ones previously considered.