基于卡尔曼滤波器和遗传算法的航空发动机性能诊断

Development of Kalman filter and genetic algorithm for aero-engine performance diagnostics

关键词:  航空发动机  性能诊断+  卡尔曼滤波  遗传算法+

Key words:  Aircraft engine  Performance diagnostics  Kalman filtering  Genetic algorithm

摘要:

以某型涡扇发动机为研究对象,构建了基于卡尔曼滤波器和遗传算法的航空发动机性能诊断方法。卡尔曼滤波器根据发动机可测参数偏离额定特性时的变化量,对发动机性能参数进行了估计。当传感器存在测量偏差时,会使滤波器估计结果偏离真实情况。遗传算法以机载模型输出与发动机测量参数之间的误差最小为目标,通过优化计算,找出存在测量偏差的传感器,确定其偏差,并最终消除测量偏差对性能诊断的影响。

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.