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Fast Precise Algorithm of Computing FRF by Considering Initial Response

机译：考虑初始响应来计算FRF的快速精确算法

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摘要

At present, the common algorithm of computing FRF is averaging method in frequency domain. This algorithm is precise method for impact exciting or burst random exciting, but not for continuous exciting, for the initial response cannot be considered. In continuous exciting test, increasing data length which permits increasing averaging times is needed to alleviate the error of FRF caused by the initial response. The initial response is caused by the previous frame of exciting force. Thus, in this work an algorithm model is put forward by considering the initial response. For each averaging computation in frequency domain, the data of two frames force and one frame response, aligned in right end, are used. The initial response is caused by the first frame force. When the FRFs of MISO are known, the IRFs (Impulse Response Function) are obtained by IFFT transform of FRFs. The theoretical response of this point except the first frame can be computed out by the convolution of forces and IRFs. The RMS of error series between theoretical response and measured response, divided by the RMS of measured response, reflects the preciseness of FRF. The smaller is the value, the better. The speed of common averaging method in frequency domain is fast, but with bad FRF preciseness when data is short. The FRF preciseness of least square devolution method in time domain is best, but with the slowest computation speed and unpractical. The preciseness of FRF with new algorithm is very near to the devolution method but the computation time can be shortened greatly. Applying the new algorithm in continuous exciting MIMO test, the test time can be greatly shortened. The new algorithm can also be applied to impact MIMO test, with multi impacts acting in different points at the same time. In the paper, real test and simulating data are used to verify the new algorithm, and the new algorithm is also compared with the time domain iteration method which is put forwarded before.
机译：目前，计算FRF的常用算法是频域中的平均方法。该算法是影响激发令人兴奋或突发的精确方法，但不需要连续令人兴奋，因为不能考虑初始响应。在连续励磁测试中，需要增加允许增加平均时间的数据长度来缓解由初始响应引起的FRF的误差。初始响应是由前一帧的兴奋力引起的。因此，在这项工作中，通过考虑初始响应来提出算法模型。对于频域的每个平均计算，使用两个帧的数据和一个帧响应，在右端对齐。初始响应是由第一帧力引起的。当已知MISO的FRFS时，IRFS（脉冲响应函数）通过​​FRF的IFFT变换获得。除第一帧之外的理论响应可以通过力和IRF的卷积来计算。理论响应与测量响应之间的误差系列的RMS除以测量响应的RMS，反映了FRF的确切性。值越小，值越好。频域中的常见平均方法的速度快，但是当数据短时间时，FRF的确切性能很差。时间域中最小二乘volution方法的FRF精确性最佳，但具有最慢的计算速度和不实验性。 FRF具有新算法FRF的精确性近于Devolution方法，但计算时间可以大大缩短。在连续令人兴奋的MIMO测试中应用新算法，测试时间可以大大缩短。新算法也可以应用于影响MIMO试验，同时在不同点处采用多次影响。在本文中，真实的测试和模拟数据用于验证新算法，并且还将新算法与以前推迟的时域迭代方法进行比较。

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