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The method of Scale - energy fuzzy clustering based on series wavelet analysis inStudying fault diagnosis of Gearbox

机译:基于串联小波分析的规模 - 能量模糊聚类方法 - 齿轮箱的故障诊断

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Vibration signals is the information carrier of gearbox working, in 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 with 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,以便监视和诊断齿轮箱运行状态。本文提出了一种基于串联小波分析处理齿轮箱振动(非静止)信号的比例 - 能量模糊聚类方法,以便我们在具有不同测量的各种运行状态下绘制信号的能量作为特征向量。因为齿轮箱中的齿轮和滚子轴承的振动信号不仅与频率有关而且时间。系列小波分析是一种时频(时间尺度)分析方法。它可以同时表达两次和频率。尺度能量的特征向量表现出与不同状态相同的状态和异化的相似性。因此,我们使用模糊聚类方法来检测和诊断不同的变速箱条件。诊断结果令人满意。它表明,系列小波分析可以为变速箱故障诊断提供令人信服的分析手段。

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