推进技术 ›› 2006, Vol. 27 ›› Issue (3): 270-275.

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基于遗传规划和线性鉴别分析的故障特征提取模型及其应用

侯胜利,李应红,尉询楷   

  1. 空军工程大学工程学院 陕西西安710038;空军工程大学工程学院 陕西西安710038;空军工程大学工程学院 陕西西安710038
  • 发布日期:2021-08-15

Feature extraction based on genetic programming and linear discriminant analysis for fault diagnosis and its application

  1. Engineering Inst.,Air Force Engineering Univ.,Xi’an 710038,China;Engineering Inst.,Air Force Engineering Univ.,Xi’an 710038,China;Engineering Inst.,Air Force Engineering Univ.,Xi’an 710038,China
  • Published:2021-08-15

摘要: 提出了一种基于遗传规划和线性鉴别分析的故障特征提取模型。该模型首先利用遗传规划从原始特征集中提取更能反映故障本质的复合特征,然后通过线性鉴别分析进行二次特征变换,消除特征之间的相关性以及压缩特征维数,得到对分类识别更有效、数目更少的特征。通过航空发动机滑油系统故障识别实验,表明经过遗传规划和线性鉴别分析提取的特征对故障具有更好的识别能力,并且对分类器具有很强的鲁棒性。

关键词: 航空发动机;故障诊断;特征提取+;遗传规划+;线性鉴别分析+

Abstract: A new feature extraction model based on genetic programming and linear discriminant analysis in fault diagnosis is proposed.In this model,genetic programming is first used to construct compound features from original feature set.Then linear discriminant analysis is employed to get rid of the correlation among features and reduce the dimension of features.Thus the more effective and smaller subset of features for classification can be gained.Fault recognition experiments in aeroengine lubricating oil system are carried out to test the performance of this model.Practical results show that the extracted features based on genetic programming and linear discriminant analysis have better recognition ability and they are robust for various classifiers.

Key words: Aeroengine;Fault diagnosis;Feature extraction~+;Genetic programming~+;Linear discriminant analysis~+