• 한국산학기술학회논문지
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• 제14권12호
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• pp.6114-6118
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• 2013

본 연구에서는 초음파 탐상시험의 펄스 반사법으로 각각 용접결함에 따른 초음파 펄스파형모형을 연구하였다. 균열은 예리하고 선명한 신호들을 발생한다. 탐촉자를 결함주위로 이동하면 에코높이는 변한다. 긴 균열에서는 탐촉자가 결함 주위를 원형으로 목돌림주사법을 사용하여 탐상하면 에코높이는 급격히 감소한다. 그 에코 봉우리는 바늘과 같이 얇고 날카롭다. 기공은 단일 결함으로부터 발생하는 에코는 예리하고 선명하다 하지만 집단의 기공들은 다수의 반사들이 중첩되고 트레이스가 들쭉날쭉한 에코가 발생한다. 슬래그 개재물은 크랙과 슬래그 결함위치에서 각각 목돌림 주사법을 사용하여 탐상하면 그 에코형상은 어느 정도 차이를 볼 수 있었다. crack은 그 에코높이가 급격히 변하는 반면에 슬래그 개재물은 증가${\rightarrow}$감소${\rightarrow}$증가${\rightarrow}$감소된다. 또한 다수 밀집된 기공의 위치에서 결함은 대표적 에코형상과 같은 잡다한 에코형상은 슬래그에서는 볼 수 없었다. 용입불량은 결함의 에코형상은 크랙과 같이 날카롭고 예리하게 나타났고, crack과 비슷한 에코형상은 갖고 있었다.

• 한국공작기계학회논문집
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• 제13권5호
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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.

• 한국생산제조학회지
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• 제19권3호
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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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• 제3권4호
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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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• 제2권6호
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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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• 제9권3호
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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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• 제75권6호
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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.

• 대한치과의사협회지
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• 제55권8호
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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.

• 한국콘크리트학회:학술대회논문집
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• 한국콘크리트학회 2000년도 가을 학술발표회 논문집(II)
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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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• 제29권1호
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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.