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Bladed wheels damage detection through Non-Harmonic Fourier Analysis improved algorithm

机译：通过改进的非谐波傅立叶分析法检测叶片轮毂损伤

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摘要

Recent papers introduced the Non-Harmonic Fourier Analysis for bladed wheels damage detection. This technique showed its potential in estimating the frequency of sinusoidal signals even when the acquisition time is short with respect to the vibration period, provided that some hypothesis are fulfilled. Anyway, previously proposed algorithms showed severe limitations in cracks detection at their early stage. The present paper proposes an improved algorithm which allows to detect a blade vibration frequency shift due to a crack whose size is really small compared to the blade width. Such a technique could be implemented for condition-based maintenance, allowing to use non-contact methods for vibration measurements. A stator-fixed laser sensor could monitor all the blades as they pass in front of the spot, giving precious information about the wheel health. This configuration determines an acquisition time for each blade which become shorter as the machine rotational speed increases. In this situation, traditional Discrete Fourier Transform analysis results in poor frequency resolution, being not suitable for small frequency shift detection. Non-Harmonic Fourier Analysis instead showed high reliability in vibration frequency estimation even with data samples collected in a short time range. A description of the improved algorithm is provided in the paper, along with a comparison with the previous one. Finally, a validation of the method is presented, based on finite element simulations results.
机译：最近的论文介绍了用于叶片轮毂损坏检测的非谐波傅里叶分析。该技术在满足振动假设的前提下，即使在采集时间相对于振动周期较短的情况下，也显示出了估计正弦信号频率的潜力。无论如何，先前提出的算法在早期的裂缝检测中显示出严重的局限性。本文提出了一种改进的算法，该算法允许检测由于裂缝而导致的叶片振动频率偏移，该裂缝的尺寸与叶片宽度相比确实很小。可以将这种技术用于基于状态的维护，从而允许使用非接触式方法进行振动测量。固定在定子上的激光传感器可以监控所有叶片到达现场之前的所有叶片，从而提供有关车轮健康状况的宝贵信息。该配置确定了每个叶片的获取时间，该获取时间随着机器转速的增加而变短。在这种情况下，传统的离散傅立叶变换分析会导致较差的频率分辨率，不适合小频移检测。相反，即使在很短的时间范围内收集数据样本，非谐波傅立叶分析也显示出在振动频率估计方面的高可靠性。本文提供了一种改进算法的说明，并与前一种算法进行了比较。最后，基于有限元仿真结果，对该方法进行了验证。

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