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Application of Vibration Signals for the Quantitative Analysis of the Optimal Threshold of Bearing Failure
Shock and Vibration ( IF 1.6 ) Pub Date : 2021-02-23 , DOI: 10.1155/2021/6653595
YaoChi Tang, Kuohao Li

This study established the prognostics and health management system for bearing failure. The vibration signals measured during the bearing operation were used for prognostics. First, the time-domain signal of vibration was calculated through generalized fractal dimensions, and the relationship diagram of generalized fractal dimensions and time was obtained. Then, the trend of bearing failure was compared by the GFDal results. However, the results can only be used for qualitative feature extraction. The bearing failure at the beginning cannot be determined by qualitative methods. Therefore, this study further converted the calculation results of GFDs into a Gauss distribution curve based on the statistical method under normal operation of the bearing. The Gauss distribution curve of the bearing under normal operation and at different time was overlapped. The overlap rate of the bearing area under different times was calculated. The minimum value was taken as the diagnostic standard, which was the optimal threshold of bearing failure defined in this study and was used as the quantitative basis for bearing failure. Therefore, the comparison of the area overlap rate under the Gauss distribution curve between the normal bearing and the bearing under test could provide diagnosis to the bearing failure. Moreover, the time point of the initial failure of the bearing could also be estimated based on the optimal failure threshold.

中文翻译:

振动信号在轴承失效最佳阈值定量分析中的应用

本研究建立了轴承故障的预测和健康管理系统。轴承运行过程中测得的振动信号用于预测。首先,通过广义分形维数计算出振动的时域信号,得到广义分形维数与时间的关系图。然后,通过GFDal结果比较了轴承失效的趋势。但是,结果只能用于定性特征提取。起初的轴承失效不能通过定性方法确定。因此,本研究基于统计方法,在轴承正常运行的情况下,将GFD的计算结果进一步转换为高斯分布曲线。正常工作和不同时间的轴承高斯分布曲线重叠。计算了不同时间的轴承区域的重叠率。将最小值作为诊断标准,这是本研究中定义的最佳轴承失效阈值,并用作轴承失效的定量基础。因此,比较正常轴承和被测轴承在高斯分布曲线下的面积重叠率可以为轴承故障提供诊断。此外,还可以基于最佳故障阈值来估计轴承初始故障的时间点。这是本研究中确定的最佳轴承失效阈值,并用作轴承失效的定量基础。因此,比较正常轴承和被测轴承在高斯分布曲线下的面积重叠率可以为轴承故障提供诊断。此外,还可以基于最佳故障阈值来估计轴承初始故障的时间点。这是本研究中确定的最佳轴承失效阈值,并用作轴承失效的定量基础。因此,比较正常轴承和被测轴承在高斯分布曲线下的面积重叠率可以为轴承故障提供诊断。此外,还可以基于最佳故障阈值来估计轴承初始故障的时间点。
更新日期:2021-02-23
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