Using High-speed Digital Image Correlation to Determine the Damping Ratio

Huňady, Róbert; Hagara, Martin; Schrštter, Martin

doi:10.1016/j.proeng.2012.09.510

Cited by 14 publications

(6 citation statements)

References 2 publications

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“…This approach was able to predict the location of varying levels of damage in the form of a crack of a certain depth. Huňady et al 33 used Q-450 Dantec Dynamics camera to estimate damping of a steel plate where the data FIGURE 1 A schematic of various nextgeneration sensing technology used in the SHM were captured at a rate of 1,000 fps. Trebuňa and Hagara 34 proposed a modification of a high-speed correlation system to estimate the modal parameters of steel plates.…”

Section: Camera-based Literaturementioning

confidence: 99%

A literature review of next-generation smart sensing technology in structural health monitoring

Sony

Laventure

Sadhu

2019

Struct Control Health Monit

375

183

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Summary Advent of computationally efficient smartphones, inexpensive high‐resolution cameras, drones, and robotic sensors has brought a new era of next‐generation intelligent monitoring systems for civil infrastructure. Vibration‐based condition assessment has garnered as a prominent method of evaluating the health of large‐scale infrastructure. The use of contact‐based sensors for acquiring vibration data becomes uneconomical and tedious due to their instrumentation cost, centralized nature, and densification required to collect sufficient data for system identification of modern complex structures. A need to advance and develop alternative methods for efficient sensing system results in next‐generation measurement technology of structural health monitoring. The abundance of handheld smartphones with easily programmable framework has helped in modifying relevant software to acquire vibration data using embedded sensors in the smartphone. The inexpensive cameras have been used to capture images and videos that are utilized to understand the structural behavior with the aid of advanced signal processing techniques. The inaccessible components of structures require noncontact sensors such as unmanned aerial vehicles (UAVs) or so‐called drones and mobile sensors to acquire structural data. To the authors' knowledge, this paper first time presents a comprehensive review of a suite of next‐generation smart sensing technology that has been developed in recent years within the context of structural health monitoring. The state‐of‐the‐art methods have been presented by conducting a detailed literature review of the recent applications of smartphones, UAVs, cameras, and robotic sensors used in acquiring and analyzing the vibration data for structural condition monitoring and maintenance.

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Section: Camera-based Literaturementioning

confidence: 99%

A literature review of next-generation smart sensing technology in structural health monitoring

Sony

Laventure

Sadhu

2019

Struct Control Health Monit

375

183

View full text Add to dashboard Cite

show abstract

“…Based on the previous research, 50–58 the authors intend to present their first experiences in the analysis of the fatigue phenomenon by combined TA and digital image correlation (DIC) methodologies. The novelty of the work is linked to the assessment of the hysteresis areas in a more exact quantitative way, with respect to those values calculated using the testing machine parameters, and comparing them with the energy detected by the thermographic methodology.…”

Section: Introductionmentioning

confidence: 99%

Energetic analysis of fatigue hysteresis by thermographic and digital image correlation methodologies

Rosa

Savio

Giudice

et al. 2020

Fatigue Fract Eng Mat Struct

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A hysteresis cycle can define the variation in mechanical characteristics of fatigue life and failure response. Traditional analysis is performed using forcedisplacement signals derived from the testing equipment, but this approach is prone to large errors due to clearances and slips in the measuring chain. For this reason, the authors here propose a novel setup able to assess accurately the strain status of specimens by digital image correlation (DIC) and a procedure to calculate the hysteresis energy by thermographic analysis in order to measure the damping energy with precision. The results obtained by an experimental investigation on a common austenitic steel (AISI 304) highlight that the hysteresis areas defined by the DIC displacements, and those found by the testing machine outputs have substantial differences in value. The thermal variations and the areas of the hysteresis loops, both linked to the plastic energy, were also compared, showing a reliable correlation.

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“…Automatic process and analysis of large volumes of images from different angles were studied as a vision-based technique for crack identification by Yeum and Dyke [61]. FFT algorithm combined with digital image correlation (DIC) data was recommended by Huňady et al [62] in order to experimentally determine the damping ratio value in steel structures. Target-tracking DIC was used in Ngeljaratan and Moustafa [63], who presented a large-scale laboratory application where DIC was utilized to monitor the response of a bridge structure and identify various modal properties, such as natural frequency, damping ratio, and mode shapes.…”

Section: Camera-based Techniquementioning

confidence: 99%

Recent Advancements in Non-Destructive Testing Techniques for Structural Health Monitoring

et al. 2021

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Structural health monitoring (SHM) is an important aspect of the assessment of various structures and infrastructure, which involves inspection, monitoring, and maintenance to support economics, quality of life and sustainability in civil engineering. Currently, research has been conducted in order to develop non-destructive techniques for SHM to extend the lifespan of monitored structures. This paper will review and summarize the recent advancements in non-destructive testing techniques, namely, sweep frequency approach, ground penetrating radar, infrared technique, fiber optics sensors, camera-based methods, laser scanner techniques, acoustic emission and ultrasonic techniques. Although some of the techniques are widely and successfully utilized in civil engineering, there are still challenges that researchers are addressing. One of the common challenges within the techniques is interpretation, analysis and automation of obtained data, which requires highly skilled and specialized experts. Therefore, researchers are investigating and applying artificial intelligence, namely machine learning algorithms to address the challenges. In addition, researchers have combined multiple techniques in order to improve accuracy and acquire additional parameters to enhance the measurement processes. This study mainly focuses on the scope and recent advancements of the Non-destructive Testing (NDT) application for SHM of concrete, masonry, timber and steel structures.

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Using High-speed Digital Image Correlation to Determine the Damping Ratio

Cited by 14 publications

References 2 publications

A literature review of next-generation smart sensing technology in structural health monitoring

A literature review of next-generation smart sensing technology in structural health monitoring

Energetic analysis of fatigue hysteresis by thermographic and digital image correlation methodologies

Recent Advancements in Non-Destructive Testing Techniques for Structural Health Monitoring

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