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Quantitative Study on the Modal Parameters Estimated Using the PLSCF and the MITD Methods and an Automated Modal Analysis Algorithm

机译:使用PLSCF估计的模态参数的定量研究及MITD方法及自动模态分析算法

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There are many advanced algorithms used to estimate modal parameters. In this paper, the modal parameters extracted from the Poly-reference Least Squares Complex Frequency (PLSCF) algorithm and the Multi-reference Ibrahim Time Domain (MITD) algorithm, are compared. The former, is widely used in the industry and is known to produce almost crystal clear stabilization diagrams with barely any spurious pole estimates. The latter, is less common and the stabilization diagrams typically contain some spurious pole estimates. An Automated Modal Analysis (AMA) algorithm, that utilizes the statistical representation of the pole estimates combined with a number of decision rules based on the Modal Assurance Criteria (MAC), is employed, to detect probable physical poles. Simulated data from a Plexiglas plate is used in the study. Results indicate that the absolute bias error associated with the modal parameter estimates output by the PLSCF algorithm is higher than the bias error related to the modal parameter estimates output by the MITD algorithm. It was not conclusive which of the two methods that had the lowest random error. It should also be mentioned that, while the MITD algorithm could process all references and responses, the PLSCF algorithm relied strongly on a delicate selection of representative references and that not too many references were used.
机译:有许多高级算法用于估计模态参数。在本文中,比较了从聚参考最小二乘复杂频率(PLSCF)算法和多参考IBrahim时域(MIT)算法中提取的模态参数。前者广泛应用于该行业,并已知几乎可以产生几乎具有几乎任何杂散的杆估计的晶体清晰的稳定图。后者不太常见,稳定图通常包含一些杂散极估计。采用自动模态分析(AMA)算法,该算法利用极估计的统计表示与基于模态保证标准(MAC)的多个决策规则相结合,以检测可能的物理杆。来自Plexiglas板的模拟数据用于研究。结果表明,与PLSCF算法输出的模态参数估计相关联的绝对偏置误差高于MITD算法输出的模态参数估计相关的偏置误差。它并不完全是随机误差最低的两种方法中的哪一种。还应该提到的,虽然MIT算法可以处理所有参考和响应,但PLSCF算法强烈依赖于精致的代表参考,而不是使用太多的参考。

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