Identification of base‐excited structures using output‐only parameter estimation

This paper presents a new identification technique for the extraction of modal parameters of structural systems subjected to base excitation. The technique uses output‐only measurements of the structural response. A combined subspace‐maximum likelihood algorithm is developed and applied to a three‐degree‐of‐freedom simulation model. Five ensembles of synthetically generated input signals, representing varying input characteristics, are employed in Monte Carlo simulations to illustrate the applicability of the method. The technique is able to circumvent some of the difficulties arising from short data sets by employing the Expectation Maximization (EM) algorithm to refine the subspace state estimates. This approach is motivated by successful application by previous authors on speech signals. Results indicate that, for certain system characteristics, more accurate pole estimates can be identified using the combined subspace‐EM formulation. In general, the damping ratios of the system are difficult to identify accurately due to limitations on data set length. The applicability of the technique to structural vibration signals is illustrated through the identification of seismic response data from the Vincent Thomas Bridge. Copyright © 2003 John Wiley & Sons, Ltd.     

A reassessment of dynamic characteristics of the Quincy Bayview Bridge using output‐only identification techniques

A reassessment of the dynamic characteristics of the 542 m cable‐stayed Bayview Bridge in Quincy, Illinois, is presented using a newly developed output‐only system identification technique. The technique is applied to an extensive set of ambient vibration response data acquired from the bridge in 1987. Vertical, torsional and transverse modal frequencies of the deck are identified, and uncertainty in damping values are estimated using an automated procedure on several redundant measurements at four locations. Important practical implementation issues associated with the implementation of the procedure and selection of algorithm design parameters for stochastic subspace identification techniques are discussed. An overall mean and standard deviation of damping of 1.0±0.8% is estimated considering all identified vertical, torsional and transverse modes in the 0–2 Hz band. The mean damping for the fundamental vertical mode (0.37 Hz) is identified as 1.4±0.5%, and for the first coupled torsion–transverse mode (0.56 Hz) is identified as 1.1±0.8%. Variability in the damping estimates is shown to decrease as estimated modal RMS acceleration levels increase. Standard deviations on estimated damping range from 0.05% to 2%. The results are shown to be a substantial improvement in the evaluation of damping compared to earlier spectral analysis conducted on the same data set. Copyright © 2005 John Wiley & Sons, Ltd.     

Data recording and processing for high-resolution frequency analysis

This paper discusses the practical considerations associated with analyzing analog data signals to very high resolution in frequency. In the problem considered here, the data set is recorded on analog tape, digitized, and processed on a digital computer. A primary concern is that recorder speed variations, or flutter, can produce artifacts which might become evident when high-resolution spectral analysis is performed. This study concludes that fractional millihertz analysis resolution can be achieved with existing analog tape recorder technology. Another problem which must be considered is the efficient storage of the large data sequences resulting from processing long-time signal records. The use of two-stage frequency analysis is described as an approach to addressing this problem. Finally, the implementation issues associated with the periodogram and AR (autoregressive) estimation algorithms are outlined. It is anticipated that the discussion of practical considerations given here will be useful to researchers who must address problems that are similar to those cited in this paper.