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RESEARCH INTO THE USE OF FRACTAL GEOMETRY FOR CONDITION MONITORING OF MACHINERY

机译:分形几何学在机械状态监测中的应用研究

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摘要

A new method of condition monitoring is proposed. Wavelet transform and fractal geometry are the means. A variety of condition monitoring techniques are currently in use for diagnosis of machinery faults. However, little research into the detection of fractal characteristics in processing signals has been done. This paper establishes wavelet transformation based on the noise signal for analysis of the correlation dimension of the typical working condition. Correlation dimension of the decomposing coefficient of wavelet transformation is calculated to identify the working condition. A field experiment shows the correlation dimension of similar working conditions has similar values while different working conditions show distinct characteristics. The correlation dimensions of the typical working condition of a pump plotted here have a different domain. The experimental results and correlation graph confirmed the proposed method's feasibility and validity.
机译:提出了一种状态监测的新方法。小波变换和分形几何是手段。当前,各种状态监视技术正在用于诊断机械故障。但是,关于处理信号中的分形特征检测的研究很少。本文基于噪声信号建立小波变换,以分析典型工况的相关维。计算小波变换分解系数的相关维数以识别工作条件。现场实验表明,相似工作条件下的相关维数具有相似的值,而不同工作条件下则具有不同的特征。此处绘制的泵的典型工作条件的相关尺寸具有不同的范围。实验结果和相关图证实了该方法的可行性和有效性。

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