2013
DOI: 10.1016/j.ymssp.2013.07.013
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An investigation of the effects of traffic induced local dynamics on global damping estimates using operational modal analysis

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Cited by 24 publications
(16 citation statements)
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“…Moreover, variations in natural frequencies and mode shapes that are identified from real measured data are good examples of aleatory uncertainties. Variations of identified modal properties due to environmental effects such as temperature() and traffic() are commonly observed during structural dynamic tests. Stochastic model updating methods can more efficiently manage aleatory uncertainties.…”
Section: Introductionmentioning
confidence: 99%
“…Moreover, variations in natural frequencies and mode shapes that are identified from real measured data are good examples of aleatory uncertainties. Variations of identified modal properties due to environmental effects such as temperature() and traffic() are commonly observed during structural dynamic tests. Stochastic model updating methods can more efficiently manage aleatory uncertainties.…”
Section: Introductionmentioning
confidence: 99%
“…e results for the damping ratio show as higher variability as their standard deviations indicate. is result is not surprising, and higher excitation seems to be required in order to obtain reliable measures of damping [25]. e damping values obtained by the EFDD method are even less reliable than those obtained by the SSI method, as can be extracted from their higher standard deviation values.…”
Section: Analysis and Comparison Of Resultsmentioning
confidence: 98%
“…Through a peak-picking of peaks and valleys in the selected time window, it is possible to evaluate the logarithmic decrement as δ = (2/ k ) ln ( r 0 / | r k |), where k is an integer index counter of the k th extreme of the ACF, k = 1,2,…, while r 0 and r k are the initial and the k th extreme value of the ACF, respectively. Then, a linear relation can be obtained in terms of counter k (Brewick and Smyth, 2013), as well as plotted and fitted with a straight line; its slope provides an estimate of the logarithmic decrement δ . Finally, from the estimated logarithmic decrement δ = δ q of mode q the corresponding modal damping ratio ζ q can be classically evaluated as ζq=δq/(4π2+δq 2)1/2 (Brincker et al., 2001b).…”
Section: Modal Damping Ratio Estimates By the Refined Fdd Algorithmmentioning
confidence: 99%
“…Mainly, the adoption of preselected fixed parameters (i.e. MAC value for the bell ID and selected range of amplitudes for the ACF, as explained in Section 3.1), as usually done in standard EFDD, suffers for these tough conditions (Brewick and Smyth, 2013; Magalhães et al., 2010). Also, the present use of seismic input makes it harder for the correct detection of the SDOF system associated to the identified mode.…”
Section: Modal Damping Ratio Estimates By the Refined Fdd Algorithmmentioning
confidence: 99%
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