An operational modal analysis method in frequency and spatial domain

Wang, Tong; Zhang, Lingmi; Tamura, Yukio

doi:10.1007/s11803-005-0012-0

Cited by 19 publications

(16 citation statements)

References 3 publications

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“…Other similar works have been presented by Magalhães et al [84], Soyoz et al [85], and Cismaşiu et al [86], among others. Another modification of the original FDD method is the frequency spatial domain decomposition (FSDD) [87] which uses spatial filtering to improve the estimation of modal frequencies and damping ratios.…”

Section: Fourier Transform-based Methodsmentioning

confidence: 99%

Time-frequency techniques for modal parameters identification of civil structures from acquired dynamic signals

Perez-Ramirez¹,

Amezquita-Sanchez²,

Adeli³

et al. 2016

J. vibroeng.

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A major trust of modal parameters identification (MPI) research in recent years has been based on using artificial and natural vibrations sources because vibration measurements can reflect the true dynamic behavior of a structure while analytical prediction methods, such as finite element models, are less accurate due to the numerous structural idealizations and uncertainties involved in the simulations. This paper presents a state-of-the-art review of the time-frequency techniques for modal parameters identification of civil structures from acquired dynamic signals as well as the factors that affect the estimation accuracy. Further, the latest signal processing techniques proposed since 2012 are also reviewed. These algorithms are worth being researched for MPI of large real-life structures because they provide good time-frequency resolution and noise-immunity.

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Section: Fourier Transform-based Methodsmentioning

confidence: 99%

Time-frequency techniques for modal parameters identification of civil structures from acquired dynamic signals

Perez-Ramirez¹,

Amezquita-Sanchez²,

Adeli³

et al. 2016

J. vibroeng.

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“…where s r and v r are, respectively, the singular value and singular vector, and N is the number of dominant singular values. In Wang et al (2005), the mode indicator function (MIF) is defined as the singular values computed from the response spectrum matrix at each spectral line. The peaks detected in the MIF plot indicate the existence of modes, and the frequencies corresponding to those peaks are known as the modal frequencies.…”

Section: Theoretical Backgroundmentioning

confidence: 99%

“…Therefore, the strain FSDD ODS can also be obtained from the frequency and spatial domain decomposition of the strain response spectrum matrix. Moreover, the similar procedures as those in the FSDD literature (Wang et al, 2005) can be applied to obtain the modal frequencies and damping ratios from the strain response spectrum matrix.…”

Section: Theoretical Backgroundmentioning

confidence: 99%

“…The data are typically a measure of surface motion and can be in displacement, velocity, or acceleration units. In this article, the strain measurement data are utilized for the ODS analysis, and a new method based on the frequency and spatial domain decomposition (Wang et al, 2005) is proposed to obtain the frequency domain strain ODSs, which allows to investigate the structural dynamic behaviors at a specific frequency clearly. The theoretical background of extraction of the ODS is first presented.…”

Section: Introductionmentioning

confidence: 99%

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Damage detection of a bridge model based on operational dynamic strain measurements

Wang

Celik

Çatbaş

2016

Advances in Structural Engineering

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Vibration data analysis reserves a significant place in structural health monitoring practice since it can be employed for certain engineering problems such as locating damage and assessing damage severity by means of vibration signature interpretation. In this study, a damage detection study is carried out in light of vibration data analysis methods on a four-span bridge model by exploiting strain measurements. The concept of strain operating deflection shape along with an extraction method based on frequency and spatial domain decomposition is proposed. The damage-induced state of the bridge model is compared with the baseline state to detect and locate the damage. The result of strain analysis is also compared with acceleration analysis by simultaneous measurements of strain and acceleration. The power spectrum matrix of responses is estimated using digital signal processing principles. Besides the operating deflection shape analysis, operational modal analysis and correlation analysis of strain modes are conducted to identify and locate the damage.

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“…With a reasonable assumption that the fl oor is subjected to lateral rigid body motion, 101 "virtual measurements" are added from constrain equations. The FSDD (Frequency Spatial Domain Decomposition) identifi cation algorithm (Wang et al, 2005) is employed to identify the modes. Due to the absence of modal scaling factors in the operational modal analysis, only real but not normalized mode shapes are obtained.…”

Section: Extracting Real Modes From Operational Modal Analysis Of a 1mentioning

confidence: 99%

Extraction of real modes and physical matrices from modal testing

Wang

Zhang

Tee

2011

Earthq. Eng. Eng. Vib.

Self Cite

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A technique to extract real modes from the identifi ed complex modes is presented in this paper, which enables the normalized real mode shapes, modal masses, and full or reduced mass and stiffness matrices to be obtained. The theoretical derivation of the method is provided in detail. An 11-DOF vibration system is used to validate the algorithm, and to analyze the effects of the number of modes utilized and measurement DOFs on the extraction results. Finally, the method is used to extract real modes from both experimental modal analysis and operational modal analysis.

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An operational modal analysis method in frequency and spatial domain

Cited by 19 publications

References 3 publications

Time-frequency techniques for modal parameters identification of civil structures from acquired dynamic signals

Time-frequency techniques for modal parameters identification of civil structures from acquired dynamic signals

Damage detection of a bridge model based on operational dynamic strain measurements

Extraction of real modes and physical matrices from modal testing

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