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An Efficient Iterative Algorithm for Accurately Calculating Impulse Response Functions in Modal Testing

机译:模态测试中精确计算脉冲响应函数的高效迭代算法

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摘要

Impulse response functions (IRFs) and frequency response functions (FRFs) are bases for modal parameter identification of single-input, single-output (SISO) and multiple-input, multiple-out (MIMO) systems, and the two functions can be transformed from each other using the fast Fourier transform and the inverse fast Fourier transform. An efficient iterative algorithm is developed in this work to directly and accurately calculate the IRFs of SISO and MIMO systems in the time domain using relatively short input and output data series. The iterative algorithm can avoid the time-consuming inversion of a large matrix in the conventional least-square method for calculating an IRF, greatly reducing the computation time. In addition, a fitting index and an error energy decreasing coefficient are introduced to evaluate the accuracy in calculating an IRF and to provide the termination criterion for the iterative algorithm. A new coherence function is also introduced to evaluate the accuracy of calculated IRFs and FRFs at different spectral lines. Two examples are given to illustrate the effectiveness and efficiency of the methodology.
机译:脉冲响应函数(IRF)和频率响应函数(FRF)是单输入单输出(SISO)和多输入多输出(MIMO)系统的模态参数识别的基础,并且可以转换这两个函数使用快速傅立叶变换和快速傅立叶逆变换彼此分离。在这项工作中开发了一种有效的迭代算法,可以使用相对较短的输入和输出数据序列在时域内直接准确地计算SISO和MIMO系统的IRF。该迭代算法可以避免传统的最小二乘法计算IRF中费时的大矩阵求逆,大大减少了计算时间。另外,引入拟合指数和误差能量减小系数,以评估计算IRF的准确性,并为迭代算法提供终止准则。还引入了新的相干函数,以评估在不同光谱线上计算的IRF和FRF的准确性。给出两个例子来说明该方法的有效性和效率。

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