Blind identification of full-field vibration modes of output-only structures from uniformly-sampled, possibly temporally-aliased (sub-Nyquist), video measurements

Yang, Yongchao; Dorn, Charles; Mancini, Tyler; Talken, Zachary; Nagarajaiah, Satish; Kenyon, Garrett T.; Farrar, Charles R.; Mascareñas, David

doi:10.1016/j.jsv.2016.11.034

Cited by 107 publications

(56 citation statements)

References 42 publications

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“…, two cases were taken into account for the optimisation problems expressed by Equation (9). One was that the three modal frequencies were assumed to have the same variance and thus κ i = 1, and the other was that κ i = 0.56, 1.84, 0.6 calculated from monitored frequency variation.…”

Section: Global Fem Updatingmentioning

confidence: 99%

Level 2 safety evaluation of concrete‐filled steel tubular arch bridges incorporating structural health monitoring and inspection information based on China bridge standards

Wang³

et al. 2018

Struct Control Health Monit

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Summary Concrete‐filled steel tubular (CFST) arch bridges have been widely used in mainland China, and their systematic safety evaluation has gained increasing attention from the bridge authorities in recent years. This paper presents the framework and application of Level 2 safety evaluation of CFST arch bridges, incorporating structural health monitoring (SHM) and inspection information. In contrast with the traditional inspection‐based qualitative assessment and direct measurement‐based quantitative assessment for SHM, Level 2 safety evaluation considers the inevitable resistance deterioration and site‐specific loading under normal operation conditions. For such safety evaluations, the most important element is using the well‐established finite element modelling for representing the actual conditions as accurately as possible. Thus, in this study, component and global finite element model (FEM) updating techniques are employed to ensure the local and global behaviour of the updated FEM, through which several types of common CFST arch bridge defects are investigated and updated. Measured site‐specific live loads experienced by CFST arch bridges are considered and transformed into design loads for comparison. Unfavourable load patterns are applied to the updated FEM for structural reanalysis, to evaluate the component safety status, and gradually increasing unfavourable load patterns are applied to the FEM to perform an ultimate load‐bearing analysis to obtain the global safety reservation. Level 2 safety evaluation is conducted by considering modal parameters, displacements, fatigue damage, and component and global safety status. Level 2 safety evaluation is applied to a typical CFST arch bridge, to demonstrate the entire evaluation process and the effectiveness of the proposed safety evaluation framework.

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Section: Global Fem Updatingmentioning

confidence: 99%

Level 2 safety evaluation of concrete‐filled steel tubular arch bridges incorporating structural health monitoring and inspection information based on China bridge standards

Wang³

et al. 2018

Struct Control Health Monit

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“…[39][40][41] Lately, phase-based video motion processing technique [42][43][44] has been explored to perform structural dynamics response (displacement) measurements and output-only modal identification without the need for installing markers or speckle paints on a structure's surface, [45][46][47][48][49][50][51] as required by traditional photogrammetry techniques. The recently developed technique enables extraction and visualization of full-field structural dynamic response and modal parameters at high spatial (pixel) resolution locations in an automated manner, 41,51 even with temporally aliased (sub-Nyquist) video measurements avoiding the need of using high-speed digital video cameras. 51 Ideally, full-field strains can then be directly computed from numerical differentiation of the estimated full-field displacements.…”

Section: Introductionmentioning

confidence: 99%

“…The recently developed technique enables extraction and visualization of full-field structural dynamic response and modal parameters at high spatial (pixel) resolution locations in an automated manner, 41,51 even with temporally aliased (sub-Nyquist) video measurements avoiding the need of using high-speed digital video cameras. 51 Ideally, full-field strains can then be directly computed from numerical differentiation of the estimated full-field displacements. However, such a direct computation is extremely sensitive to noise (commonly Gaussian-type white noise), which is inevitably contained in the experimentally estimated full-field displacements.…”

Section: Introductionmentioning

confidence: 99%

Estimation of full‐field dynamic strains from digital video measurements of output‐only beam structures by video motion processing and modal superposition

Yang

Jung

Dorn

et al. 2019

Struct Control Health Monit

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Summary Strain is an essential quantity to characterize local structural behaviors and directly correlates with structural damage initiation and development that is within local regions. Strain measurement at high spatial resolution (density) locations is thus required to characterize local structural behaviors and detect potential local damage. Traditional contact‐type strain gauges are mostly discrete point‐wise sensors that can only be placed in a limited number of positions. Distributed optical fiber sensing techniques can measure strains at spatially dense measurement points, but their instrumentation is a time‐ and labor‐intensive process associated with the issue of the fragility of fibers. Noncontact optical measurement techniques, such as a family of interferometry techniques using laser beams (e.g., laser Doppler vibrometers), can provide vibration measurement at high density spatial points without the need to install sensors on the structure. However, these measurement devices are active sensing methods that are relatively expensive and vulnerable to ambient motion. Photogrammetry is an alternative noncontact optical measurement method using (passive) white‐light imaging of digital video cameras that are relatively low‐cost, agile, and provides simultaneous measurements at high spatial density locations where every pixel becomes a measurement point. Among others, digital image correlation can achieve full‐field deformation measurements and subsequently estimate the full‐field strains. However, it is computationally extensive. This study develops a new efficient approach to estimate the full‐field (as many measurement points as the pixel number of the video frame on the structure) dynamic strains at high‐spatial (pixel)‐resolution/density location points from the digital video measurement of output‐only vibrating structures. The developed approach is based on phase‐based video motion estimation and modal superposition of structural dynamic response. Furthermore, the method is augmented by a high‐fidelity finite element model, which is updated with the full‐field experimental modal parameters “blindly” identified from the video measurement of the output‐only structure. Laboratory experiments are conducted to validate the method on a bench‐scale cantilever beam structure. Results demonstrate that the full‐field dynamic strain estimated by the developed approach from the video measurement of the output‐only vibrating beam match very well those directly measured by the strain gauges (at discrete measurement points). Some factors associated with the effectiveness of the method are experimentally studied and discussed.

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“…The applied blind source separation algorithm is able to extract the modal parameters automatically, so that user supervision and calibrating the input parameters are avoided. The same authors also investigated the effect of sub-Nyquist sampling on video measurements and the PME algorithm [39]. It has been also shown that using phase-based motion magnification as a pre-processing stage can enhance the signal-to-noise ratio in specific frequency bands for 3D DIC and 3DPT [40].…”

Section: Introductionmentioning

confidence: 99%

Vibration-based damage detection in wind turbine blades using Phase-based Motion Estimation and motion magnification

Sarrafi

Mao

Niezrecki

et al. 2018

Journal of Sound and Vibration

211

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Vibration-based Structural Health Monitoring (SHM) techniques are among the most common approaches for structural damage identification. The presence of damage in structures may be identified by monitoring the changes in dynamic behavior subject to external loading, and is typically performed by using experimental modal analysis (EMA) or operational modal analysis (OMA). These tools for SHM normally require a limited number of physically attached transducers (e.g. accelerometers) in order to record the response of the structure for further analysis. Signal conditioners, wires, wireless receivers and a data acquisition system (DAQ) are also typical components of traditional sensing systems used in vibration-based SHM. However, instrumentation of lightweight structures with contact sensors such as accelerometers may induce mass-loading effects, and for large-scale structures, the instrumentation is labor intensive and time consuming. Achieving high spatial measurement resolution for a large-scale structure is not always feasible while working with traditional contact sensors, and there is also the potential for a lack of reliability associated with fixed contact sensors in outliving the life-span of the host structure. Among the state-of-the-art noncontact measurements, digital video cameras are able to rapidly collect high-density spatial information from structures remotely. In this paper, the subtle motions from recorded video (i.e. a sequence of images) are extracted by means of Phase-based Motion Estimation (PME) and the extracted information is used to conduct damage identification on a 2.3-meter long Skystream® wind turbine blade (WTB). The PME and phased-based motion magnification approach estimates the structural motion from the captured sequence of images for both a baseline and damaged test cases on a wind turbine blade. Operational deflection shapes of the test articles are also quantified and compared for the baseline and damaged states. In addition, having proper lighting while working with high-speed cameras can be an issue, therefore image enhancement and contrast manipulation has also been performed to enhance the raw images. Ultimately, the extracted resonant frequencies and operational deflection shapes are used to detect the presence of damage, demonstrating the feasibility of implementing non-contact video measurements to perform realistic structural damage detection.

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Blind identification of full-field vibration modes of output-only structures from uniformly-sampled, possibly temporally-aliased (sub-Nyquist), video measurements

Cited by 107 publications

References 42 publications

Level 2 safety evaluation of concrete‐filled steel tubular arch bridges incorporating structural health monitoring and inspection information based on China bridge standards

Level 2 safety evaluation of concrete‐filled steel tubular arch bridges incorporating structural health monitoring and inspection information based on China bridge standards

Estimation of full‐field dynamic strains from digital video measurements of output‐only beam structures by video motion processing and modal superposition

Vibration-based damage detection in wind turbine blades using Phase-based Motion Estimation and motion magnification

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