Statistical errors effect the estimated correlation function matrix in Operational Modal Analysis due to the finite time length of the sampled data. When these errors start to dominate the correlation functions, an erratic behaviour appears without any physics - this phenomenon is known as the Noise Tail. This tail region should be disregarded in an identification of modal parameters and it is possible to estimate the location of the Noise Tail for each structural mode. In this paper, an automated removal of the Noise Tail is introduced and studied and the paper finds that this removal reduces bias and random errors in identification of modal parameters for Operational Modal Analysis.
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