Operational Vision-Based Modal Identification of Structures: A Novel Framework

Heydari, Nasser; Kutz, J. Nathan; Pakzad, Shamim N.; Diplas, Panayiotis; Eshkevari, Soheil Sadeghi

doi:10.12783/shm2019/32502

Cited by 4 publications

(2 citation statements)

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“…An example of MM application for multipoint modal identification in civil structures and construction (pedestrian bridge) is presented in [ 63 ]. The results of laboratory tests of modal identification of a cantilever are presented in [ 64 ]. In [ 65 ], the results of an experiment are also presented for a pipe cross-section.…”

Section: Examplesmentioning

confidence: 99%

Motion Magnification of Vibration Image in Estimation of Technical Object Condition-Review

Śmieja

Mamala

Prażnowski

et al. 2021

Sensors

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One of the most important features of the proper operation of technical objects is monitoring the vibrations of their mechanical components. The currently significant proportion of the research methods in this regard includes a group of research methods based on the conversion of vibrations using sensors providing data from individual locations. In parallel with the continuous improvement of these tools, new methods for acquiring information on the condition of the object have emerged due to the rapid development of visual systems. Their actual effectiveness determined the switch from research laboratories to actual industrial installations. In many cases, the application of the visualization methods can supplement the conventional methods applied and, under particular conditions, can effectively replace them. The decisive factor is their non-contact nature and the possibility for simultaneous observation of multiple points of the selected area. Visual motion magnification (MM) is an image processing method that involves the conscious and deliberate deformation of input images to the form that enables the visual observation of vibration processes which are not visible in their natural form. The first part of the article refers to the basic terms in the field of expressing motion in an image (based on the Lagrangian and Eulerian approaches), the formulation of the term of optical flow (OF), and the interpretation of an image in time and space. The following part of the article reviews the main processing algorithms in the aspect of computational complexity and visual quality and their modification for applications under specific conditions. The comparison of the MM methods presented in the paper and recommendations for their applications across a wide variety of fields were supported with examples originating from recent publications. The effectiveness of visual methods based on motion magnification in machine diagnosis and the identification of malfunctions are illustrated with selected examples of the implementation derived from authors’ workshop practice under industrial conditions.

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Section: Examplesmentioning

confidence: 99%

Motion Magnification of Vibration Image in Estimation of Technical Object Condition-Review

Śmieja

Mamala

Prażnowski

et al. 2021

Sensors

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show abstract

“…At the same time, the method based on the analysis of time-domain signal of vision-based structural modal identification, the modal parameters, including high-definition mode shapes, have been obtained directly (Eshkevari et al, 2019). The research has achieved good results for small structures in the laboratory.…”

Section: Introductionmentioning

confidence: 96%

Novel Approach to Extract Dense Full-Field Dynamic Parameters of Large-Scale Bridges Using Spatial Sequence Video

Deng

Zhou

Shao

et al. 2021

Journal of Civil Engineering and Management

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This study proposes the use of a high-speed camera as a holographic visual sensor to obtain the dense full-field dynamic parameters of the main beam of a bridge by the field of view through uniaxial rotation photography. Based on the basic principle that the frequency and mode of a structure are inherent characteristics, the mode coordinates obtained from each field of view are unified, normalized, and matched according to the same name pixels to obtain the dense fullfield dynamic parameters of the entire bridge. The frequency and first three order modes of a self-anchored suspension test bridge are collected by the method proposed in this study. The frequency comparison between the accelerometers and dial gauges is within 3%, and the mode shapes are more holographic and more realistic than those obtained by limited measuring points. In addition, the difference in the curvature mode under various damage conditions obtained by limited measurement points is compared with that obtained by the method proposed in this study. Results shows that the dense full-field modal curvature difference can reflect the change in the damage location even in a low order, which means the sensitivity of the change of damage location in low-order modal.

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Performance-based post-earthquake decision making for instrumented buildings

Roohi

Hernández

2020

J Civil Struct Health Monit

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Operational Vision-Based Modal Identification of Structures: A Novel Framework

Cited by 4 publications

References 0 publications

Motion Magnification of Vibration Image in Estimation of Technical Object Condition-Review

Motion Magnification of Vibration Image in Estimation of Technical Object Condition-Review

Novel Approach to Extract Dense Full-Field Dynamic Parameters of Large-Scale Bridges Using Spatial Sequence Video

Performance-based post-earthquake decision making for instrumented buildings

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