首页> 外文会议>Proceedings of 3rd international symposium on jet propulsion and power engineering. >APPLICATION OF LEAST SQUARE SUPPORT VECTOR REGRESSION TO AEROENGINE ADAPTIVE MODELING
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APPLICATION OF LEAST SQUARE SUPPORT VECTOR REGRESSION TO AEROENGINE ADAPTIVE MODELING

机译:最小二乘支持向量回归在航空发动机自适应建模中的应用。

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In this paper a new method based on least square support vector regression is proposed for aero engine adaptive real time modeling. It is thought that output data of aero engine will bias their nominal values in any cases of non-nominal work. So the biases of output data can be used to represent the non-nominal work conditions of the aero engine. The aero engine performance parameters deterioration is obtained through the mapping relationship between the measured output biases and the aero engine performance parameters deterioration. That is based on the least square support vector regression algorithm. When the deteriorations is got, the onboard model can be modified, after this the output of onboard model are the same as those of the real aero engine, and real time onboard model has the abilities of adaptation.
机译:本文提出了一种基于最小二乘支持向量回归的航空发动机自适应实时建模方法。人们认为,在任何非标称工作的情况下,航空发动机的输出数据都会使它们的标称值产生偏差。因此,输出数据的偏差可以用来表示航空发动机的非标称工作条件。通过测量的输出偏差与航空发动机性能参数劣化之间的映射关系来获得航空发动机性能参数劣化。那是基于最小二乘支持向量回归算法。当出现恶化时,可以修改机载模型,此后机载模型的输出与真实航空发动机的输出相同,并且实时机载模型具有自适应能力。

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