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Assessing the Influence of Fourier Analysis Parameters on Short-Time Modal Parameter Extraction

机译:评估傅立叶分析参数对短时模态参数提取的影响

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It is sometimes necessary to determine the manner in which materials and structures deteriorate with respect to time when subjected to sustained random dynamic loads. In such cases a system s fatigue characteristics can be obtained by continuously monitoring its modal parameters. This allows for any structural deterioration, often manifested as a loss in stiffness, to be detected. Many common structural integrity assessment techniques make use of Fourier analysis for modal parameter extraction. For continual modal pa rameter extraction, the Fourier transform requires that a compromise be made between the accuracy of the estimates and how frequently they can be obtained. The limitations brought forth by this compromise can be significantly reduced by selecting suitable val ues for the analysis parameters, mainly subrecord length and number of averages. Fur ther improvements may also be possible by making use of spectral enhancement techniques, specifically overlapped averaging and zero padding. This paper uses the sta tistical analysis of results obtained from numerous physical and numerical experiments to evaluate the influence of the analysis parameters and spectral enhancement techniques on modal estimates obtained from limited data sets. This evaluation will assist analysts in selecting the most suitable inputs for parameter extraction purposes. The results pre sented in this paper show that when using the Fourier transform to extract modal charac teristics, any variation in the parameters used for analysis can have a significant influence on the extraction of natural frequency estimates from systems subjected to ran dom excitation. It was found that for records containing up to 10% noise, subrecord length; hence spectral resolution, has a more pronounced influence on the accuracy of modal estimates than the level of spectral averaging; therefore spectral uncertainty. It was also found that while zero padding may not increase the actual spectral resolution, it does allow for improved natural frequency estimates with the introduction of interpolated estimates at the nondescribed frequencies. Finally, it was found that for modal parameter extraction purposes (in this case natural frequency), increased amounts of overlapped averaging can significantly reduce the variance of the estimates obtained. This is particu larly useful as it allows for increased precision without compromising temporal resolution.
机译:有时有必要确定材料和结构在承受持续的随机动态载荷时随时间而变质的方式。在这种情况下,可以通过连续监视其模态参数来获得系统的疲劳特性。这允许发现通常表现为刚度损失的任何结构劣化。许多常见的结构完整性评估技术利用傅里叶分析进行模态参数提取。对于连续的模态参数提取,傅里叶变换要求在估计的准确性和获取频率之间做出折衷。通过为分析参数(主要是子记录长度和平均数)选择合适的值,可以显着减少这种折衷带来的限制。通过使用频谱增强技术(特别是重叠平均和零填充),进一步改善也是可能的。本文使用从大量物理和数值实验中获得的结果的统计分析,来评估分析参数和光谱增强技术对从有限数据集获得的模态估计值的影响。该评估将帮助分析人员选择最适合参数提取的输入。本文提供的结果表明,当使用傅立叶变换提取模态特征时,用于分析的参数的任何变化都可能对从受到随机激励的系统中提取自然频率估计值产生重大影响。结果发现,对于包含高达10%噪声的记录,子记录长度;因此,光谱分辨率比光谱平均水平对模式估计的准确性有更明显的影响;因此光谱不确定性。还发现,虽然零填充可能不会增加实际的频谱分辨率,但是通过引入未描述的频率处的插值估计,它确实允许改进的固有频率估计。最后,发现出于模态参数提取的目的(在这种情况下为自然频率),重叠平均数的增加可以显着减小获得的估计值的方差。这一点特别有用,因为它可以在不影响时间分辨率的情况下提高精度。

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