Modal Property Extraction Based on Frequency Domain Stochastic Subspace Identification

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“…Most of the researchers have tried to improve modal damping estimation by introducing a variety of techniques for modal damping estimation in FDD-type procedures such as logarithmic decrement (LogDec) method (Brincker et al, 2001a;Gade et al, 2005), Hilbert transform (HT) (Zhang & Tamura, 2003), natural excitation techniques (NExt) ie cross-covariance function, Ibrahim time domain, and Polyreference (Bajrić et al, 2015a) as well as the optimal wavelet (Tarinejad & Damadipour, 2014). Furthermore, a new approach involving hybrids or combinations of two methods together is also introduced to improve modal damping estimation such as Enhanced FDD Algorithm in-operation modal appropriation (EFDD-INOPMA) (Ghalishooyan et al, 2019), Frequency Domain Decomposition-Natural Excitation Technique (FDD-NExT) (Frans & Arfiadi, 2019), Frequency Domain State Space-Based Mode Decomposition Framework (Hwang et al, 2019) and Frequency Domain Stochastic Subspace Identification (Chou & Chang, 2020). However, this issue is still considered as an open problem, even though some researchers have also tried to tackle the signal processing issue by making improvements using their proposed method since, the signal processing also denoted as the contributing factor for estimation errors comprising estimates of correlation function (CF) and the spectral density (SD) (Bajric et al, 2015b).…”