基于遗传算法的航空发动机机载模型支持向量机修正方法

AGA-LSSVR compensation for on-board self tuning model of aero-engine model

航空发动机的实时模型与发动机的匹配精度直接影响着航空发动机故障诊断的精度.提出了基于自适应遗传算法的最小二乘支持向量回归机(AGA-LSSVR)方法对航空发动机机载实时模型进行修正,有效的提高了模型的匹配精度.分析了最小二乘支持向量机中的参数的选取对模型修正的影响,在参数的选取空间里采用自适应遗传算法搜索最优参数.最后,比较了Back propagation(BP)神经网络、支持向量回归机、AGA-LSSVR等方法在机载模型中的修正效果.结果表明:提出的AGA-LSSVR具有很好的修正精度,验证了修正模型的有效性.

The accuracy of aero-engine model-based fault diagnosis is directly influenced by the matching accuracy between the self tuning model and real engine.The parameter selection of support vector regression by adaptive genetic algorithms was proposed and applied to the real-time on-board self tuning model,thus effectively improving the matching accuracy.After analyzing the influences of parameter selection of support vector regression(SVR) on the performances of the SVR model,optimal parameters in the given reg...