Stabilization diagrams to distinguish physical modes and spurious modes for structural parameter identification

Wu, Chunli; Liu, Hanbing; Qin, Xuxi; Wang, Jing

doi:10.21595/jve.2017.17629

Cited by 16 publications

(3 citation statements)

References 27 publications

(36 reference statements)

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“…Figure 5 shows the stabilization diagrams obtained by applying the Direct Modal Parameter Estimation (DMPE) algorithm [24] to the frequency response function (FRF) of the road pavement acquired in the three examined input-output configurations. The criteria adopted to identify physical (i.e., stable) modes require that the difference between the solutions of two consecutive iterations is lower than 1% for the frequency and 5% for the damping ratio [23,25]. Stable modes are represented as blue markers in the diagrams of figure 5.…”

Section: Resultsmentioning

confidence: 99%

An experimental approach for in-situ characterization of dynamic dissipative properties of road pavements

Loi,

Marongiu,

Rombi

et al. 2024

IOP Conf. Ser.: Mater. Sci. Eng.

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The dissipative properties of road pavements may have beneficial effects to reduce vehicle vibrations, traffic noise, vehicles-structure dynamic interaction, and degradation of pavement materials. Assessing the dissipative capacity and the damping properties of road pavements is, therefore, of critical importance. Such assessment has been mainly conducted in recent years by laboratory-scale dynamic experiments, while little effort has been devoted to in-situ tests. The latter are, in fact, cumbersome for practical reasons and typically require a more advanced data analysis when highly coupled modes of vibration are involved. Due to the heterogeneity of the road structure, classical methods are not capable of accurately estimating the road damping properties. The present study proposes an alternative experimental approach based on recording signals from accelerometers embedded in the road, which is impacted by an instrumented hammer. The data are analyzed both in the frequency and in the time domains through the combined use of stabilization diagrams and energy decay tools. Multi-mode fitting algorithms are employed to construct stabilization diagrams for the identification of resonance frequencies, while energy decay curves allow for a robust evaluation of the damping values at the identified frequencies. The effectiveness of the approach was assessed on an asphalt road structure.

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Section: Resultsmentioning

confidence: 99%

An experimental approach for in-situ characterization of dynamic dissipative properties of road pavements

Loi,

Marongiu,

Rombi

et al. 2024

IOP Conf. Ser.: Mater. Sci. Eng.

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“…Physical singular values should be separated from spurious (mathematical) singular values related to the noise in this process that defines the model order of the system [23]. From a practical point of view, the elimination of spurious modes may be performed using stabilization diagrams [27]. In the numerical simulations shown in Secs.…”

Section: Advantages and Summary Of The Steps For The Proposed Methodsmentioning

confidence: 99%

On the Combination of Random Matrix Theory With Measurements on a Single Structure

Igea

Chatzis

Cicirello

2022

ASCE-ASME Journal of Risk and Uncertainty in Engineering Systems, Part B: Mechanical Engineering

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An approach is proposed for the evaluation of the probability density functions (pdfs) of the modal parameters for an ensemble of nominally identical structures when there is only access to a single structure and the dispersion parameter is known. The approach combines the Eigensystem Realization Algorithm on sets of dynamic data, with an explicit non-parametric probabilistic method. A single structure, either a mathematical model or a prototype, are respectively used to obtain simulated data or measurements that are employed to build a discrete time state-space model description. The dispersion parameter is used to describe the uncertainty due to different sources such as the variability found in the population and the identification errors found in the noisy measurements from the experiments. With this approach, instead of propagating the uncertainties through the governing equations of the system, the distribution of the modal parameters of the whole ensemble is obtained by randomising the matrices in the state-space model with an efficient procedure. The applicability of the approach is shown through the analysis of a 2D0F mass-spring-damper system and a cantilever system. These results show that if the source of uncertainty is unknown and it is possible to specify an overall level of uncertainty, by having access to a single system measurements' it is possible to evaluate the resulting pdfs on the modal parameters. It was also found that high values of the dispersion parameter may lead to non-physical results such as negative damping ratios values.

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“…SSI is recognized as the most powerful ambient modal analysis technique (Van Overschee and De Moor, 1996). The development of weight matrices for project matrices and methods for stabilization diagrams (e.g., classical and clustering techniques) are among the major approaches to reducing uncertainty of SSI methods (Mrabet et al, 2014; Wu et al, 2017).…”

Section: Introductionmentioning

confidence: 99%

System identification of Karun IV Dam using balanced stochastic subspace algorithm considering the uncertainty of results

Pourgholi

Tarinejad

Khabir

et al. 2022

Journal of Vibration and Control

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Uncertainty in modal characteristics due to output-only system identification methods has been a challenge in operational modal analysis. The present study aims to extract modal parameters of Karun IV Dam (the highest arch dam in Iran) using the balanced stochastic subspace identification (B-SSI) and investigate the influence of user-defined parameters (i.e., columns and block rows of Hankel Matrix) on the uncertainty of the results. The effects of noise caused by numerical instabilities were first filtered using the inverse process by the condition number. Subsequently, the modal properties were homogenized with spatial clustering of applications with noise (DBSCAN) to remove the outlier and spurious characteristics. Then, the physical modes were validated by inspecting the complexity of the mode shapes based on the mode complexity factor criterion. Finally, the coefficient of variation (CV) of the validated clusters was employed to conduct a sensitivity analysis performed concerning the dimensions of the Hankel matrix to find the optimal models (with the minimum error in estimating the modal characteristics). The results indicated that the proposed method prevented the emergence of computational and noisy modes by regulating the extracted models, such that the first model of the structure was extracted with an error of less than 10% compared to the numerical model.

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Stabilization diagrams to distinguish physical modes and spurious modes for structural parameter identification

Cited by 16 publications

References 27 publications

An experimental approach for in-situ characterization of dynamic dissipative properties of road pavements

An experimental approach for in-situ characterization of dynamic dissipative properties of road pavements

On the Combination of Random Matrix Theory With Measurements on a Single Structure

System identification of Karun IV Dam using balanced stochastic subspace algorithm considering the uncertainty of results

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