Review of digital image correlation application to large-scale composite structure testing

Janeliukštis, Rims; Xiao, Chen

doi:10.1016/j.compstruct.2021.114143

Cited by 94 publications

(23 citation statements)

References 56 publications

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“…An artificial speckle pattern or the natural texture on the surface of a structure is essential for the application of DIC as a carrier of deformation information, which enables tracking of the motion of the pixels of concern from the reference image of the deformed substrate. [ 25 ] Conventionally, a speckle pattern is created by spraying black or white paint depending on the color of the substrate, which results in variations in the local intensity. The variations in local intensity are an important trait that the DIC algorithm processes to find the transformed position after deformation.…”

Section: Resultsmentioning

confidence: 99%

Digital Image Correlation Compatible Mechanoluminescent Skin for Structural Health Monitoring

et al. 2022

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Monitoring structural health using mechanoluminescent (ML) effects is widely considered as a potential full‐field and direct visualizing optical method with high spatial and temporal resolution and simple setup in a noncontact manner. The challenges and uncertainties in the mapping of ML field to effective strain field, however, tend to limit significant commercial ML applications for structural health monitoring systems. Here, however, quantification problems are resolved using the digital image correlation (DIC) method. Specifically, an image containing mechanically induced photon information is processed using a DIC algorithm to measure the strain field components, which enables the establishment of a calibration curve when the ML field is mapped onto the effective strain field using pixel level information. The results show a linear relationship between effective strain and ML intensity despite the plastic flow in ML skin. Furthermore, the calibration curve allows for easy conversion of ML field to effective‐strain field at the crack‐tip plastic zone of the alloy structure, retaining its spatial resolution. The compatibility of ML skin with the DIC algorithm not only enables the quantification of the ML effects of several organic/inorganic ML materials, but may also be useful in elucidating the fundamentals of the trap‐controlled mechanism.

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Section: Resultsmentioning

confidence: 99%

Digital Image Correlation Compatible Mechanoluminescent Skin for Structural Health Monitoring

et al. 2022

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“…In summary, DIC is a full-field and non-contact technique and has the potential for large-scale composite structure testing. A stochastic speckle pattern with random grey-level variations is essential to the accuracy of the measured displacements of the DIC (Janeliukstis and Chen, 2021), and the quality of speckle pattern can affect the results of testing and evaluation. Indeed, applying a random pattern using a marker or spray paint may influence the surface conditions of composite materials (Shadmehri and Hoa, 2019).…”

Section: Digital Image Correlationmentioning

confidence: 99%

Nondestructive testing and evaluation techniques of defects in fiber-reinforced polymer composites: A review

Chen

Jin²

2022

Front. Mater.

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Fiber-reinforced polymer composites have excellent mechanical properties and outstanding development potential and are cost-effective. They have increasingly been used in numerous advanced and engineering applications as materials for wind turbine blades, helicopter rotors, high-pressure pipelines, and medical equipment. Understanding and assessing structural failure promptly in the whole lifecycle of a composite is essential to mitigating safety concerns and reducing maintenance costs. Various nondestructive testing and evaluation (NDT&E) technologies based on different evaluation principles have been established to inspect defects under different conditions. This paper reviews the established types of NDT&E techniques: acoustic emission, ultrasonic testing, eddy current testing, infrared thermography, terahertz testing, digital image correlation, shearography, and X-ray computed tomography, which is divided into three categories based on the operation frequency and data processing means of the output signal that is directly under analysis. We listed four types of defects/damage that are currently of great interest, namely, voids and porosity, fiber waviness and wrinkling, delamination and debonding, as well as impact damage. To identify a suitable method for different defects/damage, we performed characterization and evaluation by using these NDT&E techniques for typical defects/damage. Then, the cost, inspection speed, benefits and limitations, etc. were compared and discussed. Finally, a brief overview of the development of the technologies and their applications in the field of composite fabrication was discussed.

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“…Digital image correlation (DIC) ( Figure 5 ) is a non-contact optical technique that was used to measure in-plane (2D) or out-of-plane (3D in stereo-correlation) full-field strains on the surface of a sample under static or dynamic mechanical loads [ 39 , 40 , 41 ]. It does not directly provide insight into microscale and in-depth damage mechanisms; however, it can efficiently indicate zones of high-strain localisation that would correspond to mesoscopic or macroscopic damage locations in composite materials.…”

Section: Surface Non-destructive Testing Techniquesmentioning

confidence: 99%

Non-Destructive Health Monitoring of Structural Polymer Composites: Trends and Perspectives in the Digital Era

Chaki

Krawczak

2022

Materials

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Non-destructive testing (NDT) techniques are usually used for the characterisation of defects arising in polymer composites during manufacturing or in-service use. However, each of these NDT techniques cannot always allow a full diagnosis of the material’s or component’s structural health. Thus, several techniques have to be combined in order to improve the diagnosis of the damaged state of composite structures and their evolution during the part’s life span. This opinion paper proposes a critical overview of the use and applicability of these NDT techniques for the detection and characterisation of damage to structural composite materials in view of in-service performance assessment and residual durability prognosis. It also addresses some current trends of structural health monitoring (SHM) of these materials, such as sensor–actuator embedding and NDT data fusion, and draws future perspectives on how composite SHM could evolve in the digital era, taking advantage of artificial intelligence, Internet of Things and big data to implement digital twins.

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Review of digital image correlation application to large-scale composite structure testing

Cited by 94 publications

References 56 publications

Digital Image Correlation Compatible Mechanoluminescent Skin for Structural Health Monitoring

Digital Image Correlation Compatible Mechanoluminescent Skin for Structural Health Monitoring

Nondestructive testing and evaluation techniques of defects in fiber-reinforced polymer composites: A review

Non-Destructive Health Monitoring of Structural Polymer Composites: Trends and Perspectives in the Digital Era

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