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首页> 外文期刊>Mechanical systems and signal processing >Selection of effective singular values using difference spectrum and its application to fault diagnosis of headstock
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Selection of effective singular values using difference spectrum and its application to fault diagnosis of headstock

机译：利用差分谱选择有效奇异值及其在主轴箱故障诊断中的应用

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摘要

The noise reduction effect of singular value decomposition (SVD) relies on the selection of effective singular values. The characteristic of singular values of normal signal and noise being studied, it is pointed out that there is a sudden change in the singular values of normal signal, but not in the ones of noise. The concept of difference spectrum of singular value is put forward, which consists of the forward differences of singular value sequence and can describe the sudden change status of singular values of a complicated signal. The automatic selection of effective singular values can be realized by the peak of the difference spectrum. If the maximum peak of difference spectrum is located in the first coordinates, it means that a strong direct current (DC) component is contained in original signal and the number of effective singular values will be determined by the second maximum peak coordinates, while what the first singular value corresponds to is the DC component, or else the number of effective singular values is determined by the maximum peak coordinates. The relationship between column number of matrix and noise removing quantity of SVD is also studied using difference spectrum and the result shows that this relationship is like a symmetrical parabola. By dint of the difference spectrum, the hidden modulation feature caused by gear vibration in headstock is isolated from a turning force signal and the fault gear is accurately located by this modulation feature.
机译：奇异值分解（SVD）的降噪效果取决于有效奇异值的选择。研究了正常信号和噪声的奇异值的特性，指出正常信号的奇异值有突然的变化，而噪声中没有。提出了奇异值差异谱的概念，它由奇异值序列的正向差异组成，可以描述复杂信号奇异值的突变状态。有效奇异值的自动选择可以通过差谱的峰值来实现。如果差谱的最大峰值位于第一坐标中，则表示原始信号中包含强直流（DC）分量，有效奇异值的数量将由第二最大峰值坐标确定，而第一奇异值对应于DC分量，否则有效奇异值的数量由最大峰值坐标确定。利用差谱研究了矩阵的列数与SVD去噪量之间的关系，结果表明该关系像对称抛物线。通过差异频谱，可以将车头架中的齿轮振动引起的隐藏调制特征与转向力信号隔离开，并且通过该调制特征可以精确定位故障齿轮。

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