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首页> 外文期刊>Key Engineering Materials >Development of Spike Wavelet Analysis and Its Application to Damage Analysis on Gearbox
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Development of Spike Wavelet Analysis and Its Application to Damage Analysis on Gearbox

机译：尖峰小波分析的发展及其在齿轮箱损伤分析中的应用

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Impulsive sound and vibration signals in gear system are often associated with their faults. Thus these impulsive sound and vibration signals can be used as indicators in condition monitoring of gear system. The traditional continuous wavelet transform has been used for detection of impulsive signals. However, it is often difficult for the continuous wavelet transform to identify spikes at high frequency and meshing frequencies at low frequency simultaneously since the continuous wavelet transform is to apply the linear scaling (a-dilation) to the mother wavelet. In this paper, the spike wavelet transform is developed to extract these impulsive sound and vibration signals. Since the spike wavelet transform is to apply the non-linear scaling, it has better time resolution at high frequency and frequency resolution at low frequency than that of the continuous wavelet transform respectively. The spike wavelet transform can be, therefore, used to detect fault position clearly without the loss of information for the damage of a gear system. The spike wavelet transform is successfully is applied to detection of the gear fault with tip breakage.
机译：齿轮系统中的脉冲声音和振动信号通常与故障有关。因此，这些脉冲声音和振动信号可以用作齿轮系统状态监测的指示器。传统的连续小波变换已被用于脉冲信号的检测。然而，由于连续小波变换将线性缩放（a-膨胀）应用于母小波，因此连续小波变换通常难以同时识别高频处的尖峰和低频处的啮合频率。在本文中，尖峰小波变换被开发来提取这些脉冲声音和振动信号。由于尖峰小波变换将应用非线性缩放，因此与连续小波变换相比，它在高频时的时间分辨率和低频时的频率分辨率更好。因此，尖峰小波变换可用于清晰地检测故障位置，而不会丢失齿轮系统损坏的信息。尖峰小波变换成功地应用于齿轮尖端故障的齿轮故障检测。

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