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In this study, PCA (principal component analysis) was used to select features and eliminate the redundancy features in process of rolling bearing fault monitoring. And then a new method was mentioned out to optimize the feature space with P-PCA (parts principal component analysis), which needs to deal with the data of each fault categories with PCA firstly, and then reconstructed the feature space...
In this study, a new method was mentioned out to optimize the feature space with P-PCA(Parts Principal Component Analysis), which needs to deal with the data of each fault categories with PCA firstly, and then rebuild the feature space with parts principal components which were got previously. And all this were based on PCA (Principal Component Analysis), which aim at feature selection and redundancy...
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