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转子故障的连续小波尺度谱特征提取新方法
New approach of features extraction for rotor faults from continuous wavelet transform scalogram
【摘要】 引入图像分析方法,提出了直接从转子故障信号连续小波尺度谱中提取图像纹理特征的新方法.首先,通过转子故障模拟实验台采集了不平衡、不对中、碰摩及油膜涡动等典型故障信号;然后,分析了故障信号尺度谱的差别及所提取出的数字特征对故障的敏感性;最后用结构自适应集成神经网络进行了智能诊断实验,结果表明了本文所提出的尺度谱数字特征对转子故障诊断的有效性.
【Abstract】 By introducing the image analysis method,this paper proposed a new method of directly extracting the image text features from scalogram of continuous wavelet transform of rotor faults signals.Firstly,the rotor fault experimental rig was used to simulate unbalance,misalignment,rubbing and oil whirling faults,and faults samples were obtained;secondly,the scalograms of typical faults was analyzed,and the sensitivity of digital features of scalograms to faults was studied;finally,the integrated back propagation(BP) neural network was used to carry out the diagnosis based on digital features of scalogram.The results fully show the effectivity of the new digital features of scalogram put forward in this paper.
【Key words】 continuous wavelet transform(CWT); scalogram; feature extraction; rotor; fault diagnosis; image analysis;
- 【文献出处】 航空动力学报 ,Journal of Aerospace Power , 编辑部邮箱 ,2009年04期
- 【分类号】TH17
- 【被引频次】12
- 【下载频次】342