在此基础上，研究了用球结构支持向量机作分类器，对滚动轴承内圈故障的劣化程度进行识别的理论和方法。

Basing on these, study theory and method of using Sphere-structured Support Vector Machines to recognize the roll bearing inside track's fault deterioration extent.

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结果表明，支持向量机在滚动轴承故障诊断中有很出色的分类能力。

The result showed SVM have a good performance in rolling bearing fault diagnosis.

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