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An optimized rational fraction polynomial approach for modal parameters estimation from FRF measurements

机译:一种从FRF测量估计模态参数的优化有理分数多项式方法

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This paper presents an Optimized Rational Fraction Polynomial (ORFP) approach for modal parameters estimation from the measurements of the Frequency Response Function (FRF). Although this approach is based on the Rational Fraction Polynomial (RFP) technique described in [1], it suggests the use of a constrained optimization scheme rather than the Forsythe method to overcome the short-comings of the Forsythe method. The latter are the estimation of modal parameters that do not necessarily describe a stable system and the estimation of fictitious natural frequencies. The formulation of the constrained optimization problem is presented and discussed. The assessment of the performance of the ORFP approach showed that it is better than the RFP approach in terms of its ability to identify modal parameters that ensure a stable system and its flexibility in selecting and setting the natural frequencies of the system. Several illustrative examples are given to demonstrate the robustness of the ORFP approach.
机译:本文提出了一种从频率响应函数(FRF)的测量值进行模态参数估计的优化有理分数阶多项式(ORFP)方法。尽管此方法基于[1]中描述的有理分数多项式(RFP)技术,但它建议使用约束优化方案而不是Forsythe方法来克服Forsythe方法的缺点。后者是不一定描述一个稳定系统的模态参数的估计和虚拟自然频率的估计。提出并讨论了约束优化问题的公式。对ORFP方法性能的评估表明,在确定模式参数以确保系统稳定的能力以及在选择和设置系统固有频率方面的灵活性方面,它比RFP方法更好。给出了几个说明性示例,以证明ORFP方法的鲁棒性。

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