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Application of tempered stable distribution for selection of optimal frequency band in gearbox local damage detection

机译:回火稳定分布在齿轮箱局部损伤检测中选择最佳频段的应用

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Local damage detection methods based on the vibration signal analysis are widely discussed in the literature. One of the most popular approach is signal enhancement by filtering focused on extraction of informative content at so called informative frequency band (IFB). In such approach the vibration signal first is decomposed into time-frequency representation and then the measures of impulsivity are applied to the appropriate sub-signals. Till now, kurtosis was preferred as criterion for IFB search. However, for some cases more robust criteria should be used. Jablonski proposed to calculate kurtosis from envelope spectrum, Urbanek suggested MID (Modulation Intensity Distribution), set of alternative selectors as extension of spectral kurtosis (SK) have been defined by Obuchowski. Further extension was recently proposed by Zak, namely statistics related to a-stable distribution were used as IFB indicators. This distribution is especially important in modeling data with outliers so it was reasonable to apply this approach in the considered problem. As it was shown, the a-stable based methodology for some vibration signals more clearly indicates the IFB in contrast to the classical ones. However, in case of early stage of fault development or developed fault with high level of noise the mentioned criteria (including stability index as a measure of impulsivity) may be insufficient. It is related to the fact that cyclic impulses related to damage are often hidden in the noise (even after time-frequency decomposition). In this paper we propose to apply (instead of kurtosis or stability index) the parameters of tempered stable distribution. This distribution is an extension of the cc-stable one, however, it possesses many properties of Gaussian systems. It is associated with two parameters which may indicate properly the IFB in case of poor signalto-noise ratio. In this paper we remind the approach of IFB selection based on the kurtosis and a-stable distribution and describe how to localize the information of the fault by using tempered stable approach. The real vibration signal from gearbox is analyzed in the context of presented methodology. Finally, we examine two examples of vibration signals for which the proposed approach is superior with respect to the classical methodology. (C) 2016 Elsevier Ltd. All rights reserved.
机译:在文献中广泛讨论了基于振动信号分析的局部损伤检测方法。最受欢迎的方法之一是通过过滤来增强信号,该过滤的重点是在所谓的信息频带(IFB)上提取信息内容。在这种方法中,首先将振动信号分解为时频表示,然后将冲量的测量值应用于适当的子信号。到目前为止,峰度被认为是IFB搜索的标准。但是,在某些情况下,应使用更可靠的标准。 Jablonski提议从包络谱计算峰度,Urbanek提出MID(调制强度分布),作为替代方案的选择器集作为光谱峰度(SK)的扩展已由Obuchowski定义。 Zak最近提出了进一步扩展,即与非稳定分布有关的统计数据被用作IFB指标。这种分布在使用异常值进行数据建模时尤其重要,因此在考虑的问题中应用此方法是合理的。如图所示,针对某些振动信号的基于a稳定的方法与传统方法相比,更清楚地表明了IFB。但是,在故障发展的早期或噪声水平较高的已发展故障的情况下,上述标准(包括稳定性指标作为冲量的度量标准)可能不够充分。与以下事实有关:与损伤相关的周期性脉冲通常隐藏在噪声中(即使在时频分解之后也是如此)。在本文中,我们建议应用(而不是峰度或稳定性指数)回火稳定分布的参数。这种分布是cc稳定分布的扩展,但是,它具有高斯系统的许多特性。它与两个参数相关联,这两个参数在信噪比较差的情况下可以正确指示IFB。在本文中,我们提醒了基于峰度和非稳定分布的IFB选择方法,并描述了如何使用回火稳定方法来定位故障信息。来自变速箱的真实振动信号在所介绍的方法中进行了分析。最后,我们研究了振动信号的两个示例,相对于传统方法而言,所提出的方法要优越一些。 (C)2016 Elsevier Ltd.保留所有权利。

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