Operational modal analysis approach based on multivariable transmissibility with different transferring outputs

Araújo, Iván Gómez; Laier, José Elias

doi:10.1016/j.jsv.2015.04.024

Cited by 22 publications

(2 citation statements)

References 16 publications

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“…Araújo and Laier proposed an OMA method on the basis of the singular value decomposition of PSDT matrices with different references (PSDTM‐SVD) . Also, Araújo and Laier extended the scalar PSDT concept to multivariable PSDT by relating multiple transferring outputs . In OMA methods, although PSDT‐based OMA approach is the least sensitive to colored excitations, it is not entirely independent of external excitations.…”

Section: Introductionmentioning

confidence: 99%

Enhanced stabilization diagram for automated modal parameter identification based on power spectral density transmissibility functions

Khodaygan

2019

Struct Control Health Monit

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Operational modal analysis based on power spectral density transmissibility (PSDT) functions is a useful tool to identify the modal parameters with low sensitivity to excitations. For pole extraction from the PSDT function, a proper parametric identification method such as the polyreference least squares complex frequency-domain method or poly-Max method can be used. Then, the poles are selected from a stabilization diagram (SD) with overestimating the system model order. Therefore, spurious modes can be identified that must be distinguished and removed from the system poles. To reach this aim, many techniques have been proposed and applied. In this paper, a new algorithm is proposed to enhance the performance of the SD for automated modal parameter identification based on the PSDT. The algorithm is composed of two main phases. In the first phase, the spurious modes are discriminated from the system poles on the basis of the conventional and supplementary stability criteria. On spurious mode omission, two new criteria named "pole criterion" and "coherence criterion" are introduced and applied as the supplementary stability criteria to make a more clear SD. Then, the extracted poles are categorized in the distinct clusters through a new strategy for comparing modes. In the second phase, a novel multiscreening algorithm is implemented for the automated identification of the system poles. Accordingly, the searching and averaging processes are followed between clusters, and the poles are screened to automatically identify the system poles on the basis of the numbers of their repetition in the SD via k-means clustering algorithms. Also, to improve the accuracy of the identification, the Hilbert transform is used in the construction of the PSDT functions. Finally, to validate and demonstrate the efficiency of the proposed method, a computer simulation and an experiential case study are considered.

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Section: Introductionmentioning

confidence: 99%

Enhanced stabilization diagram for automated modal parameter identification based on power spectral density transmissibility functions

Khodaygan

2019

Struct Control Health Monit

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“…There is wide interest in the application of the transmissibility in different applications. For example, Devriendt and Guillaume, 46 Weijtjens et al, 47 and Araújo and Laier 48,49 utilized the transmissibility in the operational modal analysis. In addition, Johnson and Adams, 50 Fan et al, 51 Meruane, 52 Chesne and Deraemaeker, 53 Zhu et al, 54 Li et al, 55 Zhou et al, 56 and Schallhorn and Rahmatalla 57,58 utilized the transmissibility in damage detection and modal updating.…”

Section: Introductionmentioning

confidence: 99%

Identification of the viscoelastic boundary conditions of Euler‐Bernoulli beams using transmissibility

Qiao

Rahmatalla

2019

Engineering Reports

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A new method to identify the viscoelastic boundary conditions of Euler‐Bernoulli beams under forced response is here presented. The boundary conditions and transmissibility function with viscoelastic expressions in terms of the Green function are introduced in the identification process. Two distinct identification methods are proposed: the least squares method with singular value decomposition; and the pattern search optimization method. Three examples are reported to demonstrate the efficacy of the proposed methods. The results from the least squares method to provide accurate solutions under noise‐free conditions, but poorly perform with the addition of 1% noise. Conversely, the pattern search optimization method integrates the solutions from different frequencies and provides promising solutions, even with 50% noise. The capability of identifying complex boundary conditions under high levels of noise might open the door for the proposed method to be considered in real‐life applications of structural health monitoring and model updating with boundary conditions of beam‐like structures such as bridges.

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In-process identification of machine tool dynamics

Liu

Altintaş

2021

CIRP Journal of Manufacturing Science and Technology

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Operational modal analysis approach based on multivariable transmissibility with different transferring outputs

Cited by 22 publications

References 16 publications

Enhanced stabilization diagram for automated modal parameter identification based on power spectral density transmissibility functions

Enhanced stabilization diagram for automated modal parameter identification based on power spectral density transmissibility functions

Identification of the viscoelastic boundary conditions of Euler‐Bernoulli beams using transmissibility

In-process identification of machine tool dynamics

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