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中文摘要：
提出一种基于Volterra级数和核函数主元分析（KPCA）的故障诊断方法。在提出的方法中,首先利用量子粒子群（QPSO）算法辨识出正常、转子裂纹、转子碰摩、基座松动四种状态下的Volterra级数,然后将Volterra级数作为特征向量输入到KPCA进行训练识别。实验结果表明,提出的方法是有效的,在只考虑一阶Volterra核的情况下不能进行很好地进行识别时,可以从二阶、三阶Volterra核上来区分。
英文摘要：
A new fault diagnosis method based on Volterra series and KPCA is proposed.In this method,firstly the Volterra series of four states,i.e.normal,rotor crack,rotor rub and pedestal looseness,are identified by particle swarm optimization（QPSO） algorithm.Then the Volterra series is used as characteristic vectors to input into the kernel principal component analysis（KPCA） for training and recognition.The experiment result shows that the proposed method is very effective.The higher order Volterra kernels such as the second-order,the third-order kernels can be used for the recognition when the faults can not be distinguished readily with the use of the first-order Volterra kernel only.
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