• Proceedings of the KIEE Conference
• /
• 2007.04a
• /
• pp.29-31
• /
• 2007

In this paper we propose an directional analytic approach in image data space for X-ray image which is detected from the X-ray projection system. Such a radiographic nondestructive testing has long been used for steel-tube inspection and weld monitoring. The welded area and thickness of steel-tube are detected from gradient radiating mechanism based on the evaluation of biased X-ray source position. The welded area is an ellipse type on low contrast X-ray image including noise. Noise originates from most of elements of the system. such as shielding CCD camera, imaging screen, X-ray source, inspected object, electronic circuits and etc.. Projection incorrectness and noise influence on imaging quality is to be represented by vertical pixels' distribution. Space analysis due to vertical direction also shows the segmental possibility between regions by visual edge evaluation.

• Transactions of Materials Processing
• /
• v.16 no.4 s.94
• /
• pp.323-328
• /
• 2007

The residual stress in axial direction of the steel wires has been measured by using a method based on the combination of the focused ion beam(FIB) milling and digital image correlation(DIC) program. The residual stress is calculated from the measured displacement field before and after the introduction of a slot along the steel wires. The displacement is obtained by the digital correlation analysis of high-resolution scanning electron micrographs, while the slot is introduced by FIB milling with low energy beam. The experimental procedures are described and the feasibilities are demonstrated in steel wires fabricated with different conditions. It reveals that the tensile residual stress is formed in all steel wires and this is strongly influenced by the fabrication conditions.

• Proceedings of the KIEE Conference
• /
• 2007.04a
• /
• pp.32-34
• /
• 2007

The X-ray projection system has long been used for steel-tube inspection and weld monitoring. The thickness of tubes and welded areas is based on the evaluation of radiographic shadow projections. The traditional tangential measurement estimates the distance of border lines of the projected wall shadows of a tube onto a radiographic image detector. The detected image in which although there is a variety of noise may be sectioned into several partitions according to its specific blocks. Imaging noise originates from most of elements of the system, such as shielding CCD camera, imaging screen, X-ray source, inspected object, electronic circuits and etc. The tangential projection incorrectness and noise influence on imaging quality. In this paper we first sectionalize the X-ray image on the basis of vertical contrast difference. And next functional and statistic analysis are carried on at each region. Geometrical distance and unsharpness of the edge caused by visual evaluation uncertainties are also discussed.

• Steel and Composite Structures
• /
• v.18 no.5
• /
• pp.1103-1117
• /
• 2015

It is known that material properties, connection quality and manufacturing methods are among the important factors directly affecting the behavior of steel connections and hence steel structures. The possible performance differences between a fabricated connection and its computer model may cause critical design problems for steel structures. Achieving a reliable design depends, however, on how accurately the material properties and relevant constitutive models are considered to characterize the behavior of structures. Conventionally, the stress and strain fields in structural steel connections are calculated using the finite elements method with assumed material properties and constitutive models. Because the conventional strain gages allow the measurement of deformation only at one point and direction for specific time duration, it is not possible to determine the general characteristics of stress-strain distributions in connections after the laboratory performance tests. In this study, a new method is introduced to measure displacement distribution of simple steel welded connections under tension tests. The method is based on analyzing digital images of connection specimens taken periodically during the laboratory tension test. By using this method, displacement distribution of steel connections can be calculated with an acceptable precision for the tested connections. Calculated displacements based on the digital image correlation method are compared with those calculated using the finite elements method.

• Smart Structures and Systems
• /
• v.30 no.1
• /
• pp.17-34
• /
• 2022

For steel structures, fatigue cracks are critical damage induced by long-term cycle loading and distortion effects. Vision-based crack detection can be a solution to ensure structural integrity and performance by continuous monitoring and non-destructive assessment. A critical issue is to distinguish cracks from other features in captured images which possibly consist of complex backgrounds such as handwritings and marks, which were made to record crack patterns and lengths during periodic visual inspections. This study presents a parametric study on image-based crack identification for orthotropic steel bridge decks using captured images with complicated backgrounds. Firstly, a framework for vision-based crack segmentation using the atrous convolution-based Deeplapv3+ network (ACDN) is designed. Secondly, features on crack images are labeled to build three databanks by consideration of objects in the backgrounds. Thirdly, evaluation metrics computed from the trained ACDN models are utilized to evaluate the effects of obstacles on crack detection results. Finally, various training parameters, including image sizes, hyper-parameters, and the number of training images, are optimized for the ACDN model of crack detection. The result demonstrated that fatigue cracks could be identified by the trained ACDN models, and the accuracy of the crack-detection result was improved by optimizing the training parameters. It enables the applicability of the vision-based technique for early detecting tiny fatigue cracks in steel structures.

• Structural Monitoring and Maintenance
• /
• v.9 no.3
• /
• pp.289-303
• /
• 2022

In this study, the impact of assigned pixel labels on the accuracy of crack image identification of steel structures is examined by using an atrous separable convolution neural network (ASCNN). Firstly, images containing fatigue cracks collected from steel structures are classified into four datasets by assigning different pixel labels based on image features. Secondly, the DeepLab v3+ algorithm is used to determine optimal parameters of the ASCNN model by maximizing the average mean-intersection-over-union (mIoU) metric of the datasets. Thirdly, the ASCNN model is trained for various image sizes and hyper-parameters, such as the learning rule, learning rate, and epoch. The optimal parameters of the ASCNN model are determined based on the average mIoU metric. Finally, the trained ASCNN model is evaluated by using 10% untrained images. The result shows that the ASCNN model can segment cracks and other objects in the captured images with an average mIoU of 0.716.

• Advances in concrete construction
• /
• v.7 no.2
• /
• pp.117-126
• /
• 2019

When designing reinforced concrete (RC) members, the rebar is assumed to resist all tensile forces, but the resistance of the concrete in the tension area is neglected. However, concrete can also resist tensile forces and increase the tensile stiffness of RC members, which is called the tension stiffening effect (TSE). Therefore, this study assessed the TSE, particularly after yielding of the steel bars and the effects of the steel ratio on the TSE. For this purpose, RC member specimens with steel ratios of 2.87%, 0.99%, and 0.59% were fabricated for uniaxial tensile tests. A vision-based non-contact measurement system was used to measure the behavior of the specimens. The cracks on the specimen at the stabilized cracking stage and the fracture stage were measured with the image analysis method. The results show that the number of cracks increases as the steel ratio increases. The reductions of the limit state and fracture strains were dependent on the ratio of the rebar. As the steel ratio decreased, the strain after yielding of the RC members significantly decreased. Therefore, the overall ductility of the RC member is reduced with decreasing steel ratio. The yielding plateau and ultimate load of the RC members obtained from the proposed equations showed very good agreement with those of the experiments. Finally, the image analysis method was possible to allow flexibility in expand the measurement points and targets to determine the strains and crack widths of the specimens.

• Transactions of the Korean hydrogen and new energy society
• /
• v.30 no.5
• /
• pp.455-464
• /
• 2019

Experiments were conducted to investigate the sensitivity of steel plate oxidation with temperature in a simulated furnace. Used steel plates were a general steel and a high tensile steel. Porous media burner (PM burner) used in model furnace was made for uniform temperature profile. The surrounding temperature was controlled by adjusting the flow rate of the mixture in the combustor. Oxide layer analysis was performed using SEM image analysis and EDS line scanning. Both steel sheets showed a tendency to increase the thickness of the steel sheet surface oxide layer as the temperature increases, and it was confirmed that the flaking phenomenon in surface oxidation layer appeared when the temperature was above a certain temperature.

• Steel and Composite Structures
• /
• v.23 no.6
• /
• pp.727-736
• /
• 2017

The application of carbon fiber reinforced polymer (CFRP) in steel structures primarily includes two categories, i.e., the bond-critical application and the contact-critical application. Debonding failure and buckling failure are the main failure modes for these two applications. Conventional electrometric techniques may not provide precise results because of the limitations associated with single-point contact measurements. A nondestructive full-field measurement technique is a valuable alternative to conventional methods. In this study, the digital image correlation (DIC) technique was adopted to investigate the bond behavior and buckling behavior of CFRP-steel composite members. The CFRP-to-steel bonded joint and the CFRP-strengthened square hollow section (SHS) steel column were tested to verify the suitability of the DIC technique. The stereo-DIC technique was utilized to measure continuous deformation. The bond-slip relationship of the CFRP-to-steel interface was derived using the DIC data. Additionally, a multi-camera DIC system consisting of four stereo-DIC subsystems was proposed and applied to the compressive test of CFRP-strengthened SHS steel column. The precise buckling location and CFRP delamination of the CFRP-strengthened SHS steel column were identified. The experimental results confirm that the stereo-DIC technique can provide effective measurements for investigating the behaviors of CFRP-steel composite members.

• Journal of the Korean institute of surface engineering
• /
• v.55 no.3
• /
• pp.164-172
• /
• 2022

Hot-dip galvanized steel(GI) is widely used throughout the industry as a corrosion resistance material. Corrosion of steel is a common phenomenon that results in the gradual degradation under various environmental conditions. Corrosion monitoring is to track the degradation progress for a long time. Corrosion on steel plate appears as discoloration and any irregularities on the surface. This study developed a quantitative evaluation method of the rust formed on GI steel plate using a superpixel-based DBSCAN clustering method and k-means clustering from the corroded area in a given image. The superpixel-based DBSCAN clustering method decrease computational costs, reaching automatic segmentation. The image color of the rusty surface was analyzed quantitatively based on HSV(Hue, Saturation, Value) color space. In addition, two segmentation methods are compared for the particular spatial region using their histograms.