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Advanced detection of rolling bearing spalling from de-noising vibratory signals

机译:通过消噪振动信号高级检测滚动轴承剥落

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The aim of this article is to show the interest of spectral subtraction for the improvement of the sensitivity of scalar indicators (crest factor, kurtosis) within the application of conditional maintenance by vibratory analysis on ball bearings. The case of a bearing in good conditions of use is considered; the distribution of amplitudes in the signal is of Gaussian kind. When the bearing is damaged, the appearance of spallings comes to disturb this signal, modifying this distribution. This modification is due to the presence of periodical impulses produced each time a rolling element meets a discontinuity on its way. Nevertheless, the presence of background noise induced by random impulse excitations can have an influence on the values of these temporal indicators. The de-noising of these signals by spectral subtraction in different frequency bands allows to improve the sensitivity of these indicators and to increase the reliability of the diagnosis.
机译:本文的目的是通过球轴承的振动分析,在条件维护的应用中,显示频谱减法对提高标量指标(波峰因数,峰度)灵敏度的兴趣。考虑到轴承在良好使用条件下的情况;信号中的振幅分布是高斯型的。当轴承损坏时,剥落的出现会干扰该信号,从而改变该分布。这种修改是由于每次滚动元件遇到不连续性时都会产生周期性的脉冲。但是,由随机脉冲激励引起的背景噪声的存在可能会影响这些时间指标的值。通过在不同频带中进行频谱减法对这些信号进行降噪,可以提高这些指标的灵敏度并提高诊断的可靠性。

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