• Journal of the Korea Academia-Industrial cooperation Society
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• v.14 no.12
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• pp.6114-6118
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• 2013

This study examined the ultrasonic pulse reflection method(UPRM) for testing each ultrasonic pulse waveform model(UPWM) based on weld defects. The sharp crack of a clear signal was generated. The echo height of the defective probes changed according to the location. In a long crack in a circle around the defective probes, the Swivel scanning echo height when using the particle was reduced drastically. The peaks in the echo were thin because the needle was pointed. The porosity defects arising from a single echo was sharp and crisp, but a number of pores of the collective reflection overlapped and ajagged echo was observed. Slag, slag inclusions, cracks, and defects at the Swivel scan of each particle using the echo shape showed difference in the degree. Cracks were revealed as sudden changes in the echo height of the slag inclusions: increase ${\rightarrow}$ decrease ${\rightarrow}$ increase ${\rightarrow}$ decrease. In addition, the location of a number of defects in the dense pore geometry, such as a typical echo sundry, revealed the shape in the slag. Poor penetration of the defect echo, revealed the cracks to have a sharp-edged, crack-like shape with an echo.

• Transactions of the Korean Society of Machine Tool Engineers
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• v.13 no.5
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• pp.87-95
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• 2004

From the results of AE(Acoustic Emission) source location occurred by the spot exciting as suggested in this research, it has been confirmed that AE technique is quite fruitful in figuring out the location of the occurrence, form, size and direction of the defects. As the results of examining the distribution of event for the angle of crack $\alpha$ to Xs and Ys, as the increases from $0^{\circ}$ ~ $90^{\circ}$, gradually changes its width from the axis Xs to the axis Ys. So event appears approximately similar in its size at the angle of crack $\alpha$=$45^{\circ}$, yet opposite when $\alpha$ is lager. It is believed that this is a phenomenon where its crack legnth $\alpha$, assumed as a planar defect, is to be prcjected toward the direction with a larger size. Thus, it is expected that the application of the experimental method suggested in this study would make it possible to identify the location of the defect in the material in the nondestructive way.

• Journal of the Korean Society of Manufacturing Technology Engineers
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• v.19 no.3
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• pp.326-333
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• 2010

In this study, DAQ and TRA modules were applied to the CFRP single specimen testing method using AE. A method for crack identification in CFRP specimens based on k-mean clustering and wavelet transform analysis are presented. Mode I on DCB under vertical loading and mode II on 3-points ENF testing under share loading have been carried out, thereafter k-mean method for clustering AE data and wavelet transition method per amplitude have been applied to investigate characteristics of interfacial fracture in CFRP composite. It was found that the fracture mechanism of Carbon/Epoxy Composite to estimate of different type of fractures such as matrix(epoxy resin) cracking, delamination and fiber breakage same as AE amplitude distribution using a AE frequency analysis. In conclusion, the presented results provide a foundation for using wavelet analysis as efficient crack detection tool. The advantage of using wavelet analysis is that local features in a displacement response signal can be identified with a desired resolution, provided that the response signal to be analyzed picks up the perturbations caused by the presence of the crack.

• Interaction and multiscale mechanics
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• v.3 no.4
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• pp.321-331
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• 2010

A new technique is proposed for bridge structural damage detection based on spatial wavelet analysis of the time history obtained from vehicle body moving over the bridge, which is different from traditional detection techniques based on the bridge response. A simply-supported Bernoulli-Euler beam subjected to a moving spring-mass unit is established, with the crack in the beam simulated by modeling the cracked section as a rotational spring connecting two undamaged beam segments, and the equations of motion for the system is derived. By using the transfer matrix method, the natural frequencies and mode shapes of the cracked beam are determined. The responses of the beam and the moving spring-mass unit are obtained by modal decomposition theory. The continuous wavelet transform is calculated on the displacement time histories of the sprung-mass. The case study result shows that the damage location can be accurately determined and the method is effective.

• Computers and Concrete
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• v.2 no.6
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• pp.481-498
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• 2005

A wavelet based approach is proposed for structural damage detection in beams, plate and delamination of composite plates. Wavelet theory is applied here for crack identification of a beam element with a transverse on edge non-propagating open crack. Finite difference method was used for generating a general displacement equation for the cracked beam in the first example. In the second and third example, damage is detected from the deformed shape of a loaded simply supported plate applying the wavelet theory. Delamination in composite plate is identified using wavelet theory in the fourth example. The main concept used is the breaking down of the dynamic signal of a structural response into a series of local basis function called wavelets, so as to detect the special characteristics of the structure by scaling and transformation property of wavelets. In the light of the results obtained, limitations of the proposed method as well as suggestions for future work are presented. Results show great promise of wavelet approach for damage detection and structural health monitoring.

• Structural Monitoring and Maintenance
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• v.9 no.3
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• pp.221-235
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• 2022

Among nondestructive damage detection methods, impedance-based methods have been recognized as an effective technique for damage identification in many kinds of structures. This paper proposes a method to detect cracks in metal structures by combining electro-mechanical impedance (EMI) responses and artificial neural networks (ANN). Firstly, the theories of EMI responses and impedance-based damage detection methods are described. Secondly, the reliability of numerical simulations for impedance responses is demonstrated by comparing to pre-published results for an aluminum beam. Thirdly, the proposed method is used to detect cracks in the beam. The RMSD (root mean square deviation) index is used to alarm the occurrence of the cracks, and the multi-layer perceptron (MLP) ANN is employed to identify the location and size of the cracks. The selection of the effective frequency range is also investigated. The analysis results reveal that the proposed method accurately detects the cracks' occurrence, location, and size in metal structures.

• Structural Engineering and Mechanics
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• v.75 no.6
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• pp.723-736
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• 2020

In this paper, acoustic emission (AE) and pattern recognition are utilized to identify the AE signal signatures caused by propagation of stress corrosion cracking (SCC) in a 304 stainless steel plate. The surface of the plate is under almost uniform tensile stress at a notch. A corrosive environment is provided by exposing the notch to a solution of 1% Potassium Tetrathionate by weight. The Global b-value indicated an occurrence of the first visible crack and damage stages during the SCC. Furthermore, a method based on linear regression has been developed for damage identification using AE data.

• The Journal of the Korean dental association
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• v.55 no.8
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• pp.542-555
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• 2017

1. Diagnosis Diagnosis of Crack, Direct pulp capping 2. Access opening Find the calcified canal orifice Removal of dentin shelf Obtaining the MB2 canal (MB2, MB3, DB2) 3. Perforation repair during endodontic treatment 4. Removal of the separated files 5. Open apex treatment 6. Void removal on CWT procedure 7. Re-endodontic treatment Removal of restorative material filled in pulp chamber Post removal Identification and removal of residual gutta-perch 8. Surgical endodontic treatment In each case will overview how to use a dental microscope.

• Proceedings of the Korea Concrete Institute Conference
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• 2000.10b
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• pp.1261-1266
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• 2000

In the impact echo method, a stress pulse is introduced into an object at on accessible surface by a transmitter. The pulse propagates into the test object and is reflected by flaws or interfaces. In this paper, void and crack locations of concrete specimens were detected using impact echo method. In their modal identification procedures, the double least squares solution for Ibrahim Time Domain technique was used.

• Smart Structures and Systems
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• v.29 no.1
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• pp.1-16
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• 2022

Despite recent breakthroughs in deep learning and computer vision fields, the pixel-wise identification of tiny objects in high-resolution images with complex disturbances remains challenging. This study proposes a modified U-net for tiny crack segmentation in real-world steel-box-girder bridges. The modified U-net adopts the common U-net framework and a novel Self-Attention-Self-Adaption (SASA) neuron as the fundamental computing element. The Self-Attention module applies softmax and gate operations to obtain the attention vector. It enables the neuron to focus on the most significant receptive fields when processing large-scale feature maps. The Self-Adaption module consists of a multiplayer perceptron subnet and achieves deeper feature extraction inside a single neuron. For data augmentation, a grid-based crack random elastic deformation (CRED) algorithm is designed to enrich the diversities and irregular shapes of distributed cracks. Grid-based uniform control nodes are first set on both input images and binary labels, random offsets are then employed on these control nodes, and bilinear interpolation is performed for the rest pixels. The proposed SASA neuron and CRED algorithm are simultaneously deployed to train the modified U-net. 200 raw images with a high resolution of 4928 × 3264 are collected, 160 for training and the rest 40 for the test. 512 × 512 patches are generated from the original images by a sliding window with an overlap of 256 as inputs. Results show that the average IoU between the recognized and ground-truth cracks reaches 0.409, which is 29.8% higher than the regular U-net. A five-fold cross-validation study is performed to verify that the proposed method is robust to different training and test images. Ablation experiments further demonstrate the effectiveness of the proposed SASA neuron and CRED algorithm. Promotions of the average IoU individually utilizing the SASA and CRED module add up to the final promotion of the full model, indicating that the SASA and CRED modules contribute to the different stages of model and data in the training process.