![]() ![]() The numerical calculations may be erroneous if the difference between values of rows and columns is too large. studied the Hankel matrix of the ERA and found that a larger Hankel matrix made the decomposition of noise much easier. In recent years, the ERA has been extensively used in output mode estimation this method has been effective in identifying the modal parameter of large-scale structures, such as offshore structural systems and roof overflow powerhouses. Chiang and Lin used the correlation between structural system response signals corresponding to stationary white noise to redefine the Markov parameter and built the generalized Hankel matrix with SVD to obtain the system modal parameter. They found that the mathematical version of the correlation function was identical to that of free response and impulse response and the modal parameter of the structure was obtained. assumed the ambient excitation to be a white noise and calculated the autocorrelation and cross-correlation functions of the response signal. proposed the improved method of ERA, that is, the eigensystem realization algorithm using data correlation (ERA/DC), which reduces the effect of noise on modal estimation using the characteristics of a correlation matrix to increase the accuracy of identification. The ERA is mathematically reasonable, but improper optimum dimension and size of the Hankel matrix will result in incorrect modal parameter estimation. In 1986, Juang and Pappa developed the eigensystem realization algorithm (ERA) based on SVD and the minimum realization algorithm. In 1974, Zeiger and McEwen proposed the concept of Singular Value Decomposition (SVD) in conjunction with the minimum realization algorithm. This method could describe the system accurately but disregarded effective estimation of impulse response with noise. In 1965, Ho and Kalman proposed the minimum realization algorithm, using the Markov parameter composed of the impulse response function to obtain the minimum-order state-space representation. The output-only modal identification can be implemented by multiple time-domain or frequency-domain methods. ![]()
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