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中文摘要：
结合Voherra级数和隐Markov模型，提出了一种基于Volterra核特征提取的HMM故障识别方法。在该方法中，利用子空间法从正常、滚动体故障、内圈故障和外圈故障4种不同的轴承中提取Volterra核作为特征向量，然后，输入到各种故障模式的HMM中进行识别。提出方法利用电机转轴末端滚动轴承采集的实验数据得到了验证。
英文摘要：
Combining voherra series with Hidden Markov Model （HMM）, a new bearing fault recognition method named Volterra kernel-HMM is proposed. vectors are extracted from from normal, ball, inner In the proposed method, the Volterra kernel feature and outer fault by the subspace method. Then these feature vectors are input the each fault HMM to recognize. The experiment result shows that the proposed method is very effective. The proposed method is tested with the experiment data sampled from drive end ball bearing of an induction motor driven mechanical system.
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