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Operational modal analysis in the presence of pulse train and harmonics based on SSI

机译:基于SSI的脉冲序列和谐波存在下的运行模态分析

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Operational Modal Analysis (OMA) is a popular and effective method to identify the dynamic characteristics of a structure for Condition Monitoring (CM). It is well known that most of OMA methods are under the assumption that the excitation loads are stationary white noise. In practice however, this is not true, the ex-citation with pulse train and harmonic loads are common for mechanical systems with rotation parts, such as wind turbine and vehicle tested on the roller rig. In order to investigate the effects of pulse train and harmonic loads on the OMA, a quarter vehicle model was developed to simulate a Y25 bogie tested on the roller rig. Moreover, Correlation signal Subset based Stochastic Subspace Identification (CoS-SSI) was employed as the OMA technique in this study. The simulation results indicated that pulse train excitation has no effects on the OMA, whereas harmonic loads have significant effects. On the one hand, harmonic loads will result in false modes, on the other hand, the harmonic frequency will overwhelm the true modes of tested systems when the harmonic frequency is close to system resonance frequency. Therefore, cepstrum editing process was introduced in de-tail, and employed to filter out the harmonic effects before the OMA process. It has been proved that cepstrum editing is an easy but powerful approach to ad-dress the challenge of OMA in the presence ofharmonics.
机译:操作模态分析(OMA)是一种流行且有效的方法,用于识别状态监测(CM)结构的动态特性。众所周知,大多数OMA方法都是在假设激励负载为平稳白噪声的前提下进行的。但是实际上,这是不正确的,对于带有旋转零件的机械系统(例如风力涡轮机和在压路机上测试过的车辆),通常采用脉冲串和谐波负载进行励磁。为了研究脉冲序列和谐波负载对OMA的影响,开发了四分之一车辆模型来模拟在滚轴钻机上测试的Y25转向架。此外,在这项研究中,基于相关信号子集的随机子空间识别(CoS-SSI)被用作OMA技术。仿真结果表明,脉冲串激励对OMA没有影响,而谐波负载则有显着影响。一方面,谐波负载将导致错误的模式,另一方面,当谐波频率接近系统谐振频率时,谐波频率将使被测系统的真实模式不堪重负。因此,详细介绍了倒谱编辑过程,并在OMA处理之前将其用于滤除谐波效果。已经证明,倒谱编辑是解决谐波存在下OMA挑战的一种简单而有效的方法。

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