关键词: 航空发动机;性能诊断+;卡尔曼滤波;遗传算法+

Abstract: An aero-engine performance diagnostic method,based on Kalman filter and genetic algorithm,is investigated.Sensor measurement deviations from nominal condition are the only information for estimation of engine health parameters.They are often distorted by sensor biases,thereby masking the true condition of engine and leading to incorrect diagnostic result.Genetic algorithms are applied for sensor bias detection and estimation.Then the engine health parameters can be estimated accurately by Kalman filter with the biased free measurement deviations. The performance of the hybrid method is evaluated through a case study of a turbofan engine simulation.The results show that this approach is promising for reliable diagnostics of aero-engines.

Key words: Aircraft engine;Performance diagnostics;Kalman filtering;Genetic algorithm