夏遵平, 王彤. 谐波噪声下的试验模态分析[J]. 工程力学, 2018, 35(3): 235-241. DOI: 10.6052/j.issn.1000-4750.2016.11.0867
引用本文: 夏遵平, 王彤. 谐波噪声下的试验模态分析[J]. 工程力学, 2018, 35(3): 235-241. DOI: 10.6052/j.issn.1000-4750.2016.11.0867
XIA Zun-ping, WANG Tong. EXPERIMENTAL MODAL ANALYSIS IN CONSIDERATION OF HARMONIC NOISE[J]. Engineering Mechanics, 2018, 35(3): 235-241. DOI: 10.6052/j.issn.1000-4750.2016.11.0867
Citation: XIA Zun-ping, WANG Tong. EXPERIMENTAL MODAL ANALYSIS IN CONSIDERATION OF HARMONIC NOISE[J]. Engineering Mechanics, 2018, 35(3): 235-241. DOI: 10.6052/j.issn.1000-4750.2016.11.0867

谐波噪声下的试验模态分析

EXPERIMENTAL MODAL ANALYSIS IN CONSIDERATION OF HARMONIC NOISE

  • 摘要: 试验模态分析中通常使用平均方法处理由实验环境引起的随机噪声。当测试环境中含有周期噪声时,很难通过平均方法去除,在频响函数中会产生虚假共振峰,影响结构参数识别精度。该文提出了基于增强概率统计的谐波响应检测方法,将物理坐标下的响应信号变换到模态坐标中,并根据谐波信号的统计特性检测出谐波成分。提出了一种基于谐波分解与重构的谐波去除方法,用于消除谐波成分对结构参数识别的影响。通过平面刚架的仿真算例和GARTEUR飞机模型实测算例阐明了提出方法的实现过程,验证了其可靠性。

     

    Abstract: In experimental modal analysis (EMA), the average approach is generally used to process the random noise in vibration signals. In many cases, the problem of harmonic components, which may be caused by periodic excitation to structures, is difficult to solve by the average approach, and this can lead to erroneous modal identification. In this paper, an optimized harmonic indicator function named enhanced probability statistics (EPS) was proposed to improve the effectiveness of harmonic component detection. Moreover, a new algorithm based on the harmonic decomposition was presented to remove the harmonic components before modal estimation. The presented method was validated by a simulation example of a plane frame and a practical modal test of the GARTUER plane model. Compared with the method based on experimental modal analysis without considering harmonic excitation, the new method offers better and more reliable parameter identification.

     

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