Gray fault diagnosis method based on LSA and SVM

摘要：

In order to solve the application problems of gray relation theory and support vector machine in fault diagnosis, the paper introduces a new method, which combines latent semantic analysis with support vector machine. With latent semantic analysis realizing sample data feature extraction and dimensionality reduction to solve the training and diagnosing speed problem resulted from a number of high-dimensional sample data. And with principle of gray relation analysis to solve the classification problems which support vector machine can not achieve. Applying the method to fault diagnosis for a certain type of aircraft, the accuracy could reach to more than 94％, and the experimental results demonstrates the superiority of the presented method and its applied value.

关键词： fault diagnosis grey relation theory support vector machine

作者: Hu Mingjie He Yuzhu Li Jianhong

作者单位: Dept.of System Engineering of Engineering Technology,Beijing University of Aeronautics and Astronautics,Beijing,China

会议类型: 国际会议

会议名称: 2009 IEEE International Conference on Intelligent Computing and Intelligent Systems(2009 IEEE 智能计算与智能系统国际会议)

会议地点: 上海

会议语种:英文

页码: 108-112

在线出版日期: 2009-11-20（万方平台首次上网日期，不代表论文的发表时间）