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On the basis of vibration signal of rolling bearing, a new method of fault diagnosis based on K-L transformation and Lagrange support vector regression is presented.Multidimensional correlated variable is transformed into low dimensional independent eigenvector by the means of K-L transformation. The pattern recognition and nonlinear regression are achieved by the method of Lagrange support vector...
In this paper, a new method of fault diagnosis based on K-L transform and support vector machine(SVM) is presented on the basis of statistical learning theory and the feature analysis of vibrating signal of ball bearing. The key to the fault bearings diagnosis is feature extracting and feature classifying. Multidimensional correlated variable is converted into low dimensional independent eigenvector...
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