【摘要】 针对振动信号的非线性特征,提出一种基于等距特征映射(Isometric feature mapping,ISOMAP)和支持矢量机(Support vector machine,SVM)的转子故障诊断方法。利用ISOMAP把数据从高维空间投影到低维空间而不改变数据内在属性的特点,对高维的故障振动信号降维并提取出低维的数据作为特征矢量,采用一种新核函数支持矢量机作为分类器进行故障诊断。将该方法应用于转子故障诊断,结果表明,ISOMAP-SVM方法不仅具有较高的故障诊断率,而且取得振动信号在低维空间的可视化表示。与其他核函数相比新核函数支持矢量机具有较好的诊断效果。更多还原

【Abstract】 Aiming at the non-linear characteristics of vibration signals,a method of fault diagnosis of turbine rotor based on isometric feature mapping(ISOMAP) and support vector machine(SVM) is proposed.For the advantages of ISOMAP that it can maintain the inner feature while projecting the high dimension data onto low dimension data space.The vectors form low dimension data space are extracted,which produced by ISOMAP from high dimension space of vibration signal,and consider them as feature vectors,adopting a new kernel function SVM classifier to diagnosis fault types.The proposed ISOMAP-SVM approach is applied to the rotor fault diagnosis.The results show that this method has higher fault diagnosis accuracy,it can make a visual outcome of fault diagnosis.Compared with other kernel functions,the new kernel function SVM has better diagnosis effect.更多还原