Fault detection and diagnosis in turbine engines using fuzzy logic

In this paper, we present a fuzzy logic based method of fault detection and diagnosis in gas turbine engines. The fuzzy logic system rule base is derived using heuristics extracted from designed experiments and flight data representing component performance changes due to field service degradation. The fuzzy logic rule based method incorporates both sensed engine parameters that represent non-deteriorated engine operation and fault conditions related to engine performance such as high pressure turbine, high pressure compressor and combustor deterioration. The fuzzy logic system is evaluated using residuals calculated based on both empirical models as inputs. The efficacy of the fuzzy logic system in detecting and diagnosing engine faults is demonstrated using field test data. We also examine performance robustness in the presence of varying levels of sensor noise and measurement errors.