基于EMD-SVM镜像延拓的转子故障诊断研究

利用EMD算法把机械中转子的振动信号进行分解,通过镜像延拓法对EMD算法产生的端部效应进行抑制,得到若干个能够反映转子故障信号内在变化特征及变化规律的固有模态函数分量;对每一个固有模态函数分量建立AR模型,将模型的自回归参数和残差的方差作为故障特征向量,以此建立SVM分类器并进行故障类型识别。结果表明,基于EMD-SVM镜像延拓的方法能够准确快速地得到转子故障的特征和状态,增加了转子故障诊断系统的可靠性和实用性。

Research of the rotor fault diagnosis based on mirror extension of EMD-SVM

The vibration signal of the mechanical rotor was decomposed by the EMD method,and the end effect produced was restrained through mirror extension.Then,several intrinsic mode functions which reflected the inherent variation characteristics and regulations of rotor fault signal were obtained.The AR models of each component were established,and the auto-regressive parameters,the variance of remnant of the AR models were regarded as the fault feature vectors,and the SVM classifier was built to recognize the fault pattern.The results show that the rotor fault diagnosis based on mirror extension of EMD-SVM could obtain the accurate characteristics and status of the rotor fault system,and increase the reliability and availability of the rotor fault system.