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Recurrence plot entropy for machine defect severity assessment

机译:递归图熵用于机器缺陷严重性评估

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This paper presents a nonlinear time series analysis technique for evaluating machine defect severity, based on the Recurrence Plot (RP) entropy. The RP entropy is calculated from the probability distribution of the diagonal line length in the recurrence plot, which graphically depicts a system's dynamics and provides a global picture of the autocorrelation in a time series over all available time-scales. Results of experimental studies conducted on a spindle-bearing test bed have demonstrated that, as the working condition of the bearing deteriorates due to the initiation and/or progression of structural damages, the frequency information contained in the vibration signal becomes increasingly complex, leading to the increase of the RP entropy. As a result, RP entropy can serve as an effective indicator for defect severity assessment of rolling bearings.
机译:本文提出了一种基于递归图(RP)熵的非线性时间序列分析技术,用于评估机器缺陷的严重性。 RP熵是根据递归图中对角线长度的概率分布计算得出的,该图以图形方式描绘了系统的动力学,并提供了在所有可用时间范围内的时间序列中自相关的全局图。在主轴轴承试验台上进行的实验研究结果表明,由于轴承的工作条件由于结构损坏的发生和/或进行而恶化,因此振动信号中包含的频率信息变得越来越复杂,导致RP熵的增加。结果,RP熵可作为评估滚动轴承缺陷严重性的有效指标。

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