Fault diagnosis in gas turbine engines using fuzzy logic

This paper describes a fuzzy logic-based method of fault detection and diagnosis in gas turbine engines. The fuzzy logic rule base is derived using heuristics based on designed experiments and flight data. The method is evaluated using model-based residuals and calculated values as inputs. The efficacy of the system is demonstrated using flight data. This paper describes how to augment a limited number of input parameters by combining them with the rates of change of the normal input parameters and other derived parameters. This augmented parameter set enables a better estimate of the prediction horizon for diagnosis. The paper also presents a case study where high-pressure spool deterioration is detected about two months prior to engine failure. Although, the system is demonstrated using the example of high pressure spool deterioration it can be applied to engine failures with similar characteristics.