中文摘要：

针对转盘轴承故障样本少、信号微弱且不易提取的特点,提出了一种双谱分析和支持向量机相结合的故障诊断方法。首先采用双谱分析提取特征向量,然后利用支持向量机对转盘轴承正常、外圈故障、单个螺栓断裂、多个螺栓断裂4种状态进行分类和识别。结果表明：该方法分类结果的总体准确率为86%,基本有效可行,但精度仍需进一步提高。

英文摘要：

The slewing bearings are characterized with small fault samples,weak signals and difficult extraction,a fault diagnosis method is proposed based on bispectrum analysis and support vector machine（ SVM）. Firstly,the feature vector is extracted by using bispectrum analysis. Then the normal state,outer ring fault,single bolt fracture and multiple bolt fracture of slewing bearings are classified and identified by using SVM. The results show that the classification result has a total accuracy of 86%. The method is essentially effective and feasible,but the precision still need to improve.