转子系统典型故障的小波包分形特征  

Characteristic study of typical faults of rotor systems combining wavelet packet with fractal

作　　者：冯成付 杨丽晶[2] 钟声[3] 

机构地区：[1]大庆炼化公司机动处,黑龙江大庆163411 [2]大庆油田有限责任公司采油工程研究院,黑龙江大庆163453 [3]大庆石油管理局钻井工程技术研究院,黑龙江大庆163413

出　　处：《大庆石油学院学报》2007年第5期85-87,共3页Journal of Daqing Petroleum Institute

基　　金：黑龙江省教育厅科学技术研究项目(10541010)

摘　　要：针对转子系统碰摩、质量不平衡、油膜涡动等典型故障,根据小波包和分形理论在多尺度分析和自相似本质上的一致性,给出小波包分解和关联维数相融合的故障特征提取方法,即对转子系统的振动信号进行小波包分解,将计算分解系数的关联维数作为故障特征向量,然后通过神经网络进行识别.结果表明,利用文中提出的故障特征提取方法,可以对转子系统故障进行有效诊断.Based on the natural consistence of wavelet packet and fractal theory on the multi scales analysis and self-similarity, this paper presents a method of fault characteristics extraction combining the wavelet packet decomposition with the correlation dimension for several typical fault (such as friction, mass imbalance and oil film whirling) of rotor system. Firstly, the wavelet packet is applied to decompose the vibration signal, and the correlation dimensions of decomposition coefficient obtained are regarded as characteristic vector of fault, then the characteristic vector of fault is identified by neural network. The simulation result verifies that the method presented by this paper is very effective for several typical fault diagnoses of rotor system.

关 键 词：转子 小波包 分形 特征提取 故障诊断 

分 类 号：TP206[自动化与计算机技术—检测技术与自动化装置]