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•Vision-based modal parameter identification was assessed for bridge structural health monitoring.•HVS and identification algorithms were developed for structural damage ...detection.•The superiority of vision-based modal parameters in damage detection was demonstrated.•Improved sensor efficiency and reduced cost responses were demonstrated.
Noncontact monitoring using holography can be quite useful in vision-based structural health monitoring owing to its advantages in terms of data visualization and real-time applications. Aimed at exploring the potential of vision-based sensors for structural health monitoring in more general applications, this paper has developed the holographic visual sensor (HVS) with a vision-based modal parameter identification method. This strategy is an extension of the current vision-based techniques and holography. Based on the newly introduced spatial and temporal sequence data measured by HVS, the vision-based modal parameter identification method was proposed and applied to structural health monitoring for the first time. Accordingly, the feature point set describing the geometric morphology of the structural holography and the time-state-space mathematical model of the structural dynamics system was constructed. In this way, the mechanical behavior characteristics could be extracted from serial transient holographic responses following excitation, and the structural modal parameters were then calculated and quantitatively analyzed. Laboratory experiments and field tests were employed for validation based on the comparison between the results determined by the proposed HVS and those determined by conventional, high-precision contact sensors. The developed HVS and identification algorithms were able to visually collect and identify modal parameters at a higher data resolution and provide smoother modal shapes. The proposed method can thus be used to complement and improve existing computer-vision-based measurement techniques and damage detection.
The accurate estimation of natural frequencies and damping ratios is critical for civil structures. In this article, a method based on short-time narrow-banded mode decomposition is proposed to ...analyze the modal parameters of civil structures. In this approach, short-time narrow-banded mode decomposition is applied to identify time-varying structures with free vibration responses. On the contrary, by analysis of the weighting factors α and β, short-time narrow-banded mode decomposition is improved to estimate the parameter of time-invariant systems. In the case of enhanced short-time narrow-banded mode decomposition, the original short-time narrow-banded mode decomposition approach is modified in two ways. First, the instantaneous frequency term of the objective function is removed, and one weighting factor remains, that is, α in the objective function. Second, a technique is provided to automatically detect the optimum value of α. Two numerical examples, that is, a three-degree-of-freedom time-variant system and a simple model of the Lysefjord bridge are provided. In addition, an experiment with a real-life pedestrian bridge located at Tufts University, United States, is used to demonstrate the applicability of the proposed method. The analysis results indicate that the proposed method can easily identify high-quality natural frequencies and damping ratios.
In the wind tunnel test, the full-bridge aeroelastic model needs to simulate both the shape and dynamic characteristics of the real bridge, and modal parameters are key dynamic parameters. Therefore, ...it is essential to identify the modal parameters of the model accurately. To get accurate modal parameters of the long-span bridge model in the wind tunnel test, the applications of the Hilbert-Huang transform for modal parameter identification were analyzed in this paper. Then a band-pass filter is designed to filter the original signal so that the intrinsic mode function obtained by empirical mode decomposition can satisfy the single-component signal requirement and eliminate the mode mixing effect effectively. Meanwhile, the endpoint data extension method based on SVM (Support Vector Machine) was presented to restrain the end effects of empirical mode decomposition. Finally, taking the Oujiang Bridge as the engineering background, the improved algorithm was applied to modal parameter identification of the bridge under ambient excitation. The modal parameters such as modal frequency and damping ratio were obtained. The reliability of the improved method was verified by comparing the identified modal parameters with the results of the finite element method, and it turns out that the improved method can reduce the frequency identification error of vertical bend, lateral bend, and torsion to 1.01%, 4.07%, and 1.68%. The results indicated that the improved method based on the Hilbert-Huang transform can accurately identify the main modal parameters of the structure and can be better applied to identify the modal parameters of long-span bridge structures.
An out-put only modal parameter identification method based on variational mode decomposition (VMD) is developed for civil structure identifications. The recently developed VMD technique is utilized ...to decompose the free decay response (FDR) of a structure into to modal responses. A novel procedure is developed to calculate the instantaneous modal frequencies and instantaneous modal damping ratios. The proposed identification method can straightforwardly extract the mode shape vectors using the modal responses extracted from the FDRs at all available sensors on the structure. A series of numerical and experimental case studies are conducted to demonstrate the efficiency and highlight the superiority of the proposed method in modal parameter identification using both free vibration and ambient vibration data. The results of the present method are compared with those of the empirical mode decomposition-based method, and the superiorities of the present method are verified. The proposed method is proved to be efficient and accurate in modal parameter identification for both linear and nonlinear civil structures, including structures with closely spaced modes, sudden modal parameter variation, and amplitude-dependent modal parameters, etc.
In this study, it is aimed to compare the modal damping ratios attained by considering the measurement duration, frequency range, sampling rate, and the method used in modal parameter identification ...as variable parameters. The investigations were performed on a 3 storey steel building model. The measurements were taken from only top floor level of the building model by using twelve uni-axial seismic accelerometers. An impact hammer with rubber tip was used to vibrate the model by generating random impacts. The measurements were repeated by taking into account four different time intervals (5–10–30–60min) using 0–12.5Hz as the base frequency range. The collected signals were analyzed within 0–6.25Hz frequency range considering the sampling rates as 512, 1024 and 2048. Both the natural frequencies and the modal damping ratios were obtained from each measurement by using Enhanced Frequency Domain Decomposition (EFDD) and Stochastic Subspace Identification (SSI) techniques. The natural frequencies and their corresponding modal damping ratios were presented and compared with each other for all cases. It was observed from the study that the change in the natural frequencies was very small while the modal damping ratios were changed considerably depending on the selected analysis options.
•The modal damping ratios of steel structures were identified by OMA.•The investigations were performed on a 3 storey steel building model.•The natural frequencies and modal damping ratios were presented.•The modal damping ratios were changed considerably.
Modal parameters, including fundamental frequencies, damping ratios, and mode shapes, could be used to evaluate the health condition of structures. Automatic modal parameter identification, which ...plays an essential role in realtime structural health monitoring, has become a popular topic in recent years. In this study, an automatic modal parameter identification procedure for high arch dams is proposed. The proposed procedure is implemented by combining the density-based spatial clustering of applications with noise (DBSCAN) algorithm and the stochastic subspace identification (SSI). The 210-m-high Dagangshan Dam is investigated as an example to verify the feasibility of the procedure. The results show that the DBSCAN algorithm is robust enough to interpret the stabilization diagram from SSI and may avoid outline modes. This leads to the proposed procedure obtaining a better performance than the partitioned clustering and hierarchical clustering algorithms. In addition, the errors of the identified frequencies of the arch dam are within 4%, and the identified mode shapes are in agreement with those obtained from the finite element model, which implies that the proposed procedure is accurate enough to use in modal parameter identification. The procedure is feasible for online modal parameter identification and modal tracking of arch dams.
This paper introduces a novel wavelet-based methodology for identifying the modal parameters of a structure in the aftermath of an earthquake. Our proposed approach seamlessly combines a subspace ...method with a stationary wavelet packet transform. By relocating the subspace method into the wavelet domain and introducing a weighting function, complemented by a moving window technique, the efficiency of our approach is significantly augmented. This enhancement ensures the precise identification of the time-varying modal parameters of a structure. The capacity of the stationary wavelet packet transform for rich signal decomposition and exceptional time-frequency localization is harnessed in our approach. Different subspaces within the stationary wavelet packet transform encapsulate signals with distinct frequency sub-bands, leveraging the fine filtering property to not only discern modes with pronounced modal interference, but also identify numerous modes from the responses of a limited number of measured degrees of freedom. To validate our methodology, we processed numerically simulated responses of both time-invariant and time-varying six-floor shear buildings, accounting for noise and incomplete measurements. Additionally, our approach was applied to the seismic responses of a cable-stayed bridge and the nonlinear responses of a five-story steel frame during a shaking table test. The identified modal parameters were meticulously compared with published results, underscoring the applicability and reliability of our approach for processing real measured data.
The rotation of spacecraft flexible appendage may cause changes in modal parameters. For this time-varying system, the computation cost of the frequently-used singular value decomposition (SVD) ...identification method is high. Some control problems, such as the self-adaptive control, need the latest modal parameters to update the controller parameters in time. In this paper, the projection approximation subspace tracking (PAST) recursive algorithm is applied as an alternative method to identify the time-varying modal parameters. This method avoids the SVD by signal subspace projection and improves the computational efficiency. To verify the ability of this recursive algorithm in spacecraft modal parameters identification, a spacecraft model with rapid rotational appendage, Soil Moisture Active/Passive (SMAP) satellite, is established, and the time-varying modal parameters of the satellite are identified recursively by designing the input and output signals. The results illustrate that this recursive algorithm can obtain the modal parameters in the high signal noise ratio (SNR) and it has better computational efficiency than the SVD method. Moreover, to improve the identification precision of this recursive algorithm in the low SNR, the wavelet de-noising technology is used to decrease the effect of noises.
•The rotation of the large flexible appendage of spacecraft is considered.•The time-varying modal parameters of this spacecraft structure are identified.•Apply recursive algorithm without SVD to determine the time-varying modal parameters.•The recursive algorithm has faster computational speed than common SVD-based methods.•The wavelet de-noising is employed to improve identification precision for lower SNR.
Modal parameter identification of systems, structures and machines with variable physical parameters is an important task for their damage diagnosis, maintenance and repair, and life cycle ...management, especially when time-varying vibration modes are involved. The paper proposes a new combined, two-step, i.e., estimated wavelet-based frequency response function (FRF) and least-squares iterative algorithm, modeling approach in order to determine time-varying vibration modes based on Gaussian white noise input excitation. The time-varying wavelet-based FRF is estimated based on output noise estimation model
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; the second step identifies time-varying modal parameters based on estimated wavelet-based FRF with the use of least-squares iterative algorithm. Estimated wavelet-based FRF can reveal the dynamic characteristics of the system correctly similar to the theoretical FRF by single degree of freedom (SDOF). The combined method is demonstrated using system identification analysis based on the simulated stiffness-varying and mass-varying multiple-degree-of-freedom (MDOF) system subjected to random Gaussian white noise excitation. The results show that the proposed combined method accurately identifies modal parameter of the time-invariant analyzed structure, and correctly captures modal parameter of the time-varying analyzed structure. The modal frequency and shape agree with theoretical results well. The analysis results also indicate that the proposed combined method is sensitive to the position of input excitation. The estimation accuracy wavelet-based FRF can be improved by selecting the average number of times and wavelet parameters.
•Structural identification by blind source separation.•ICA cannot be adopted in high damping structure (with damping ratio more than 1%).•An improved method named IDT+ICA overcomes the flaw of ICA.
...Structural modal parameter identification under ambient excitation has strong engineering value and theoretical significance. As the most popular tool for solving Blind Source Separation (BSS) problems, Independent Component Analysis (ICA) is able to directly extract the time-domain modal parameters, including frequencies, damping ratios and modal shapes. ICA, however, has a fatal flaw of failing to identify structures with higher damping. To overcome the flaw above, the paper proposes a new method named “ICA+IDT”. Firstly, free vibration response of a structure is obtained from structural outputs under ambient excitation. Inverse damping transfer (IDT) is employed to turn a highly damped signal into a low damping response signal without changing of frequencies and mode shapes. Then, structural modal parameters are extracted from the low damping response signal by ICA. Finally, the identified damping ratios are adjusted to eliminate the impact of IDT. To verify the effectiveness and applicability of IDT+ICA proposed herein, two numerical simulations—mass-spring model and simply supported concrete beam—and an experiment model of three-story steel frame are built, and the analysis results reveal that presented method can identify structures with higher damping effectively.
