Transient Responses of Conventional Filters

Henderson, K. C.; Kautz, William H.

doi:10.1109/tct.1958.1086485

Cited by 37 publications

(7 citation statements)

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“…Similarly, a lower order Butterworth filter will result in a shorter duration of ringing but with a greater amplitude of ringing. 43 More complex methodologies have been developed for minimising the effects of filtering artefacts such as the work of Gottlieb and Shu. 44 Bayesian time-domain OMA methods, as described by Yuen and Katafygiotis, 45 Yuen et al 46 and Yang et al, 47 directly avoid the introduction of filtering artefacts into the time-domain OMA as raw data are analysed without any…”

Section: Minimising the Effects Of Filtering Artefactsmentioning

confidence: 99%

Reducing coherent filtering artefacts in time‐domain operational modal analysis

Wynne

Hopgood

Stratford

2022

Structural Contr & Hlth

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Signals collected for modal analysis are often filtered in order to reduce sensor noise, out-of-band oscillations, or for dealing with closely-spaced modes. This filtering introduces filtering artefacts into the data due to the non-ideal filter response and is well understood for impulse excitation. However, for ambient vibration data filtering, artefacts become superimposed, preventing their visual identification, and will corrupt the correlation function of the data used in time-domain operational modal analysis (OMA) techniques such as covariance-driven stochastic subspace identification and the random decrement technique. This corruption leads to inaccurate, misleading, biased or spurious frequency and damping estimates, with the inaccuracy increasing for systems with higher damping or lower signal-to-noise ratios. Counterintuitively, the error in damping estimates is as large for modes with natural frequencies far from the filter cutoff frequency as for modes which are close to the cutoff frequency. In this paper, an alternative to filtering for time-domain OMA, trimming of the correlation of noise from unfiltered correlation functions, is introduced and tested using 10,000 numerically generated ambient vibration data sets. It has been shown that this technique reduces the mean absolute error in the frequency estimates by over 200% and the mean absolute error in the damping estimates by over 400%. Additionally, a new technique which incorporates fitting of filtering artefacts as part of the modal analysis is introduced for where filtering of ambient vibration data is unavoidable and is demonstrated using real-world acceleration data collected from a two-way spanning concrete slab subject to footfall excitation.

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Section: Minimising the Effects Of Filtering Artefactsmentioning

confidence: 99%

Reducing coherent filtering artefacts in time‐domain operational modal analysis

Wynne

Hopgood

Stratford

2022

Structural Contr & Hlth

View full text Add to dashboard Cite

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“…Then the parametric equations for the upper bound on A(t) are given by (4), (5), and (6) for k odd and by (4), (7), and (8) for k even, where 0 < y < 1.…”

Section: Jomentioning

confidence: 99%

“…Differentiating 14, (22), and (23) and combining them according to (24), we obtain (6) and (8). Furthermore, inserting (24) into (16), we have «" W <2»…”

Section: Jomentioning

confidence: 99%

“…Hence, equality cannot be achieved in this expression. Here, £(?/) is given by either (5) or (7) and dB/dy is the derivative of either (6) or (8). Thus, integral expressions for the lower bounds on these movements have been formulated.…”

Section: Jomentioning

confidence: 99%

“…Functions of this type are quite common in electric network theory. For instance, the reciprocals of Hurwitz polynomials are members of this class and they are used quite frequently in network synthesis [5][6][7]. The transfer functions of the series-shunt peaking network and the Dietzold network [8] are also subclass k functions.…”

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confidence: 99%

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