首页> 外文会议>International conference on signal processing systems;ICSPS 2010 >The method of Scale - energy fuzzy clustering based on series wavelet analysis in Studying fault diagnosis of Gearbox
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The method of Scale - energy fuzzy clustering based on series wavelet analysis in Studying fault diagnosis of Gearbox

机译:基于序列小波分析的尺度能量模糊聚类方法在齿轮箱故障诊断研究中的应用。

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Vibration signals is the information carrier of gearbox working, iB order to monitor and diagnose the gearbox running states. This paper proposes a method of scale energy fuzzy clustering based on series wavelet analysis processing gearbox vibration (non-stationary) signals that we draw the energy of the signal under various running states with different measurement as eigenvector. Because vibration signals of gear and roller bearings in the gearbox are not only related to frequency but also to time. Series wavelet analysis is a time-frequency (time-scale) analysis method. It can express both time and frequency in the same time. The eigenvector of scale-energy shows similarity with same state and dissimilarity witb different states. So we use the fuzzy clustering methods to detect and diagnose different conditions of gearbox. The diagnosis result is satisfactory. It shows that series wavelet analysis can supply a convincing analysis means for gearbox fault diagnosis.
机译:振动信号是变速箱工作的信息载体,iB指令用于监控和诊断变速箱的运行状态。提出了一种基于序列小波分析处理齿轮箱振动(非平稳)信号的尺度能量模糊聚类方法,该方法利用不同测量条件下的各种运行状态下的信号能量作为特征向量。因为齿轮箱中齿轮和滚动轴承的振动信号不仅与频率有关,而且与时间有关。序列小波分析是一种时频(时标)分析方法。它可以同时表示时间和频率。尺度能量的特征向量在相同状态下表现出相似性,而在不同状态下表现出相异性。因此,我们使用模糊聚类方法来检测和诊断齿轮箱的不同状况。诊断结果令人满意。结果表明,小波序列分析可以为变速箱故障诊断提供有力的分析手段。

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