Measurement and identification of the nonlinear dynamics of a jointed structure using full-field data, Part I: Measurement of nonlinear dynamics

Chen, Wei; Jana, Debasish; Singh, Aryan; Jin, Mengshi; Cenedese, Mattia; Kosova, Giancarlo; Brake, Matthew Robert; Schwingshackl, Christoph W.; Nagarajaiah, Satish; Moore, Kate; Noël, Jean-Philippe

doi:10.1016/j.ymssp.2021.108401

Cited by 22 publications

(16 citation statements)

References 59 publications

(74 reference statements)

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“…Current limitations of the present approach include weaker performance for large forcing amplitudes. These appear, for example, in the BRB experiments of [ 7 , 8 ], which we expect to capture only with a more refined forced-reduced dynamics and improved calibration procedures. The same requirement holds for more complicated forcing types (e.g.…”

Section: Discussionmentioning

confidence: 99%

“…The Brake–Reuss beam (BRB) is a benchmark system in the study of jointed structures [ 7 , 8 , 83 ]. In our study, it consists of two 304 stainless steel beams assembled with a lap joint, as shown in figure 4 a .…”

Section: Examplesmentioning

confidence: 99%

“…Low-dimensional models are expected to reduce computational cost and capture the essential physics of a high-dimensional system from data. Given the growing interest, for example, in light mechanical structures and MEMS devices, there is the need for truly nonlinear models, capturing amplitude-dependent properties and competing steady-states solutions, which are increasingly important to identify, as highlighted in experiments of nonlinear mechanical vibrations [1][2][3][4][5][6][7][8]. Predicting coexisting stable and unstable forced responses for a broad range of forcing amplitudes and frequencies is paramount in structural dynamics.…”

Section: Introductionmentioning

confidence: 99%

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Data-driven nonlinear model reduction to spectral submanifolds in mechanical systems

Cenedese

Axås

Yang

et al. 2022

Phil. Trans. R. Soc. A.

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While data-driven model reduction techniques are well-established for linearizable mechanical systems, general approaches to reducing nonlinearizable systems with multiple coexisting steady states have been unavailable. In this paper, we review such a data-driven nonlinear model reduction methodology based on spectral submanifolds. As input, this approach takes observations of unforced nonlinear oscillations to construct normal forms of the dynamics reduced to very low-dimensional invariant manifolds. These normal forms capture amplitude-dependent properties and are accurate enough to provide predictions for nonlinearizable system response under the additions of external forcing. We illustrate these results on examples from structural vibrations, featuring both synthetic and experimental data. This article is part of the theme issue ‘Data-driven prediction in dynamical systems’.

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Section: Discussionmentioning

confidence: 99%

Section: Examplesmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Data-driven nonlinear model reduction to spectral submanifolds in mechanical systems

Cenedese

Axås

Yang

et al. 2022

Phil. Trans. R. Soc. A.

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“…29,30 Instead of using the unique marker, some speckle pattern can also be created to determine the motion of cable hangers using digital image correlation (DIC). [31][32][33] But these techniques are not completely non-contact as it involves painting speckles or mounting markers on the structure. Some of the completely non-contact video-based cable response measurement techniques proposed recently are based on optical flow technique 34 and robust subpixel orientation code matching (OCM) algorithm.…”

Section: Introductionmentioning

confidence: 99%

“…Studies use the optical flow‐based methods to track a unique marker attached to stay cables to estimate the cable response 29,30 . Instead of using the unique marker, some speckle pattern can also be created to determine the motion of cable hangers using digital image correlation (DIC) 31–33 . But these techniques are not completely non‐contact as it involves painting speckles or mounting markers on the structure.…”

Section: Introductionmentioning

confidence: 99%

Computer vision‐based real‐time cable tension estimation algorithm using complexity pursuit from video and its application in Fred‐Hartman cable‐stayed bridge

Jana

Nagarajaiah

Yang

2022

Structural Contr & Hlth

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Summary Real‐time health monitoring of stay cables in cable‐stayed bridges is necessary for timely maintenance and to avoid unforeseen fatigue damage due to vortex‐induced vibration—mainly due to combination rain and wind‐related dynamic loads. Conventional contact‐based sensors may often malfunction in harsh weather conditions and are expensive to install and maintain. Therefore, recently, the usage of non‐contact camera‐based measurement is burgeoning in the domain of structural sensing. Non‐contact video‐based sensing provides a higher spatial resolution compared to conventional sensors along with a lower cost. Therefore, in this paper, we present a framework that uses video‐based measurement as multiple sensors to reduce the estimation error in determining the real‐time cable tension. First, we calculate the vibration response using the phase‐based motion estimation algorithm for various locations of interest. We then intuitively fuse the data from all the locations to estimate the real‐time frequency variation using a blind source separation (BSS) technique named complexity pursuit (CP). Finally, the real‐time stay‐cable tension is calculated from the real‐time frequency history using the taut‐string theory. The proposed algorithm is applied to Fred‐Hartman cable‐stayed bridge in Houston, Texas. The algorithm is validated using actual tension in the cable. We also show that the estimation error in the proposed sliding window‐based CP framework is considerably lesser than the conventional real‐time tension estimation technique using Short‐time Fourier Transform (STFT). The accurate estimation of stay‐cable tension from the video‐based measurement shows the significant potential of the proposed framework in the domain of structural health monitoring.

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Integrated acoustic‐vibration frequency‐modulation technology to detect the contact nonlinear features of mechanical structure

Qiu

Abbas

Zhu

et al. 2022

Structural Contr & Hlth

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Measurement and identification of the nonlinear dynamics of a jointed structure using full-field data, Part I: Measurement of nonlinear dynamics

Cited by 22 publications

References 59 publications

Data-driven nonlinear model reduction to spectral submanifolds in mechanical systems

Data-driven nonlinear model reduction to spectral submanifolds in mechanical systems

Computer vision‐based real‐time cable tension estimation algorithm using complexity pursuit from video and its application in Fred‐Hartman cable‐stayed bridge

Integrated acoustic‐vibration frequency‐modulation technology to detect the contact nonlinear features of mechanical structure

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