Output-only modal analysis for non-synchronous data using stochastic sub-space identification

Lu, Lin Jun; Hua, Zhou; Ni, Yi; Dai, Fei

doi:10.1016/j.engstruct.2020.111702

Cited by 11 publications

(3 citation statements)

References 48 publications

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“…Figure 12 shows the bufeting-induced vertical acceleration response time history of the bridge at 1/4 main span and the corresponding normalized PSD during 16:00-18:30 on June 18, 2020. Many methods can be used to identify the modal parameters from vibration signals, such as the stochastic subspace identifcation [28], the power spectral method [29], the eigensystem realization algorithm [30], the fast Bayesian FFT method [31,32], and so on. In this study, the fast Bayesian FFT method is used to identify the natural frequencies and damping ratios.…”

Section: Bridge Model Updatingmentioning

confidence: 99%

Vortex-Induced Force Identification of a Long-Span Bridge Based on Field Measurement Data

Jiang,

Xu,

Zhu

et al. 2023

Structural Control and Health Monitoring

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Vortex-induced force (VIF) identification and modelling of a long-span bridge are often conducted in terms of aeroelastic sectional model tests in wind tunnels. However, there are uncertainties inherent in wind tunnel model tests so that vortex-induced vibration (VIV) still occurs in real long-span bridges designed according to wind tunnel test results. This paper presents a framework for VIF identification of a long-span bridge based on field-measured wind and acceleration data. The framework is composed of the four steps: (1) decompose field-measured acceleration response time histories using variational mode decomposition (VMD) method; (2) obtain velocity and displacement response time histories using frequency domain integration (FDI) method; (3) establish and update the finite element model and identify the generalized VIF time histories of the bridge; and (4) identify the parameters in the polynomial VIF models and decide the most suitable VIF model. The proposed framework is finally applied to a real suspension bridge with a recent VIV event. The results show that the proposed framework can accurately identify the generalized VIF acting on the bridge from the field-measured acceleration and wind data, and the derived most suitable VIF model can produce almost the same vortex-induced response (VIR) as the measured ones.

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Section: Bridge Model Updatingmentioning

confidence: 99%

Vortex-Induced Force Identification of a Long-Span Bridge Based on Field Measurement Data

Jiang,

Xu,

Zhu

et al. 2023

Structural Control and Health Monitoring

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“…To correct time-delay-induced errors, Lei et al [15] estimated the time delay by fitting the measured data to an autoregressive model (ARX) or an average autoregressive model. Zhou et al [26] corrected the time delay by a state-space (SS) equation model combined with a data-driven stochastic subspace identification (data-driven SSI) method to calculate the mean phase deviation. These algorithms need to determine a reasonable number of model orders to obtain the real-time lag information and are too computationally complex to achieve rapid evaluation.…”

Section: Introductionmentioning

confidence: 99%

An Approach for Time Synchronization of Wireless Accelerometer Sensors Using Frequency-Squeezing-Based Operational Modal Analysis

Chen

Zheng

Luo

et al. 2022

Sensors

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Wireless sensor networks usually suffer from the issue of time synchronization discrepancy due to environmental effects or clock management collapse. This will result in time delays between the dynamic responses collected by wireless sensors. If non-synchronized dynamic response data are directly used for structural modal identification, it leads to the misestimation of modal parameters. To overcome the non-synchronization issue, this study proposes a time synchronization approach to detect and correct asynchronous dynamic responses based on frequency domain decomposition (FDD) with frequency-squeezing processing (FSP). By imposing the expected relationship between modal phase angles extracted from the first-order singular value spectrum, the time lags between different sensors can be estimated, and synchronization can be achieved. The effectiveness of the proposed approach is fully demonstrated by numerical and experimental studies, as well as field measurement of a large-span spatial structure. The results verify that the proposed approach is effective for the time synchronization of wireless accelerometer sensors.

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“…To perform vision‐based displacement measurement, the primary and possibly most crucial step is to establish the relationship between the 3D object space and the 2D image plane inside the camera to solve how the coordinates

( {x,y} )

of an image point on the image plane can be analytically transformed into its coordinates

( {X,Y,Z} )

in the object space (Baqersad et al., 2017; Park et al., 2015). In civil engineering, bridges, high‐rise buildings, and steel structures are structures that are frequently monitored (Amezquita‐Sanchez et al., 2017; Li et al., 2017; Lu et al., 2021). As these structures have dominant in‐plane displacements under external loads, measurements acquired from a camera would suffice.…”

Section: Introductionmentioning

confidence: 99%

A unified normalization method for homography estimation using combined point and line correspondences

Dai

2021

Computer aided Civil Eng

Self Cite

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Data normalization is an essential and imperative step when using the direct linear transform method for homography estimation. However, the existing data normalization methods only rely on either point coordinates or line coefficients in computing homography, which is inapplicable to many civil infrastructure scenes, in which both points and lines exist but are scarce. It is plausible to maximize the accuracy level achievable by fully utilizing all points and lines available in these scenes. To fit this purpose, this study proposed a unified data normalization method for homography estimation by processing combined point and line correspondences. In this method, an analytical procedure was created to transform line coefficients for normalization under similarity transformation. By this procedure, formulas for defining parameters of the similarity transformation were developed and equations for pre‐ and post‐processing of data were established, leading to a pipeline that allows for solving different combinations of point and line correspondences simultaneously. Both simulation experiments and field tests were conducted to evaluate the performance of the method. The results showed that the method can effectively exploit all available point and line correspondences and significantly improve the accuracy for homography estimation under different measurement conditions.

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Output-only modal analysis for non-synchronous data using stochastic sub-space identification

Cited by 11 publications

References 48 publications

Vortex-Induced Force Identification of a Long-Span Bridge Based on Field Measurement Data

Vortex-Induced Force Identification of a Long-Span Bridge Based on Field Measurement Data

An Approach for Time Synchronization of Wireless Accelerometer Sensors Using Frequency-Squeezing-Based Operational Modal Analysis

A unified normalization method for homography estimation using combined point and line correspondences

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