摘要
针对旋转机械在故障和正常状况下的旋转振动信号存在频率差异的特点,给出了差异度的信息分离方法。依据该方法筛选出有用的IMF分量,求取这些IMF分量的能量特征。把这一系列特征向量送入分类器进行分类,从而可以实时、高效的对旋转机械进行诊断,并完成故障分类。
Aiming at the fault and normal condition of rotational vibration signal in the presence of the same fre- quency and different characteristics, a difference degree separation method has presented based on the theory of Hilbert Huang transform （HHT）. Screening out the useful component IMF via the presented method, and chase down the IMF components of the energy characteristics. Then send the series of eigenvector into the classifier, which can real-time, high efficiency to the diagnosis and fault classification of the rotating machinery .
出处
《河南城建学院学报》
CAS
2012年第3期57-60,共4页
Journal of Henan University of Urban Construction
基金
河南省科技攻关项目(102102210533)
关键词
差异度
故障
IMF
特征向量
分类
Difference degree
Fauh
IMF
Eigenvector
Classification
