• Steel and Composite Structures
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• v.19 no.1
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• pp.131-152
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• 2015

Easy detection and evaluation of defect in the tube structure is a continuous problem and remains a significant demand in tube inspection technologies. This study is aimed to automate defect detection using the pattern recognition approach based on the classification of high frequency stress wave signals. The stress wave signals from vibrational impact excitation on several tube conditions were captured to identify the defect in ASTM A179 seamless steel tubes. The variation in stress wave propagation was captured by a high frequency sensor. Stress wave signals from four tubes with artificial defects of different depths and one reference tube were classified using the autoregressive (AR) algorithm. The results were demonstrated using a dendrogram. The preliminary research revealed the natural arrangement of stress wave signals were grouped into two clusters. The stress wave signals from the healthy tube were grouped together in one cluster and the signals from the defective tubes were classified in another cluster. This approach was effective in separating different stress wave signals and allowed quicker and easier defect identification and interpretation in steel tubes.

• Journal of the Korean Society for Nondestructive Testing
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• v.30 no.1
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• pp.31-35
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• 2010

This paper presents the development of automatic defect detection program using 3D computed tomography image of small solid rocker motor. We applied the neighbor pixel comparison algorithm with beam hardening correction for the recognition of defect. We made the artificial defect specimen in order to decide a standard CT value of defect. The program was tested with 150 small solid rocket motors and it could detect the disbond, crack, foreign material and void. The program showed more reliable and faster results than human inspector's interpretation.

• Journal of the Korean Society for Precision Engineering
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• v.15 no.7
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• pp.149-159
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• 1998

The importance of soundness and safety evaluation in weld zone using by the ultrasonic wave has been recently increased rapidly because of the collapses of huge structures and safety accidents. Especially, the ultrasonic method that has been often used for a major non-destructive testing(NDT) technique in many engineering fields plays an important role as a volume test method. Hence, the defecting any defects of weld Bone in austenitic stainless steel type 304 using by ultrasonic wave and neural network is explored in this paper. In order to detect defects, a distance amplitude curve on standard scan sensitivity and preliminary scan sensitivity represented of the relation between ultrasonic probe, instrument, and materials was drawn based on a quantitative standard. Also, a total of 93％ of defect types by testing 30 defect patterns after organizing neural network system, which is learned with an accuracy of 99％, based on ultrasonic evaluation is distinguished in order to classify defects such as holes or notches in experimental results. Thus, the proposed ultrasonic wave and neural network is useful for defect detection and Ultrasonic Non-Destructive Evaluation(UNDE) of weld zone in austenitic stainless steel 304.

• Journal of the Korean Society for Nondestructive Testing
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• v.27 no.4
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• pp.321-327
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• 2007

In lock-in thermography, a phase difference between the defect area and the healthy area indicates the qualitative location and size of the defect. To accurately estimate these parameters, the shearing-phase technique has been employed which gives the shearing-phase distribution. The shearing-phase distribution has maximum, minimum, and zero points that help determine quantitatively the size and location of the subsurface defect. In experiment, the proposed technique is verified with artificial specimen and these related factors are analyzed.

• Advances in nano research
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• v.16 no.1
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• pp.91-109
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• 2024

Carbon nanotubes are drawing wide attention of research communities and several industries due to their versatile capabilities covering mechanical and other multi-physical properties. However, owing to extreme operating conditions of the synthesis process of these nanostructures, they are often imposed with certain inevitable structural deformities such as single vacancy and nanopore defects. These random irregularities limit the intended functionalities of carbon nanotubes severely. In this article, we investigate the mechanical behaviour of double-wall carbon nanotubes (DWCNT) under the influence of arbitrarily distributed single vacancy and nanopore defects in the outer wall, inner wall, and both the walls. Large-scale molecular simulations reveal that the nanopore defects have more detrimental effects on the mechanical behaviour of DWCNTs, while the defects in the inner wall of DWCNTs make the nanostructures more vulnerable to withstand high longitudinal deformation. From a different perspective, to exploit the mechanics of damage for achieving defect-induced shape modulation and region-wise deformation control, we have further explored the localized longitudinal and transverse spatial effects of DWCNT by designing the defects for their regional distribution. The comprehensive numerical results of the present study would lead to the characterization of the critical mechanical properties of DWCNTs under the presence of inevitable intrinsic defects along with the aspect of defect-induced spatial modulation of shapes for prospective applications in a range of nanoelectromechanical systems and devices.

• Journal of Chest Surgery
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• v.21 no.1
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• pp.148-151
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• 1988

We experienced 2 years and 5 months old male patient with partial anomalous pulmonary venous return of the left lung into the coronary sinus without atrial septal defect. After incising the atrial septum and the wall between the left atrium and the coronary sinus, we made the roof of the coronary sinus and closed the artificial atrial septal defect, with using patch, then we could change the direction of the blood flow from the coronary sinus into the left atrium. The patient was discharged on the 13th postoperative day after uneventful postoperative course.

• Journal of Korean Society for Quality Management
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• v.51 no.1
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• pp.55-65
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• 2023

Purpose: The purpose of this study is to propose an optimization process to improve product yield in the process using process data. Recently, research for low-cost and high-efficiency production in the manufacturing process using machine learning or deep learning has continued. Therefore, this study derives major variables that affect product defects in the manufacturing process using eXplainable Artificial Intelligence(XAI) method. After that, the optimal range of the variables is presented to propose a methodology for improving product yield. Methods: This study is conducted using the injection molding machine AI dataset released on the Korea AI Manufacturing Platform(KAMP) organized by KAIST. Using the XAI-based SHAP method, major variables affecting product defects are extracted from each process data. XGBoost and LightGBM were used as learning algorithms, 5-6 variables are extracted as the main process variables for the injection process. Subsequently, the optimal control range of each process variable is presented using the ICE method. Finally, the product yield improvement methodology of this study is proposed through a validation process using Test Data. Results: The results of this study are as follows. In the injection process data, it was confirmed that XGBoost had an improvement defect rate of 0.21% and LightGBM had an improvement defect rate of 0.29%, which were improved by 0.79%p and 0.71%p, respectively, compared to the existing defect rate of 1.00%. Conclusion: This study is a case study. A research methodology was proposed in the injection process, and it was confirmed that the product yield was improved through verification.

• Journal of Periodontal and Implant Science
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• v.26 no.1
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• pp.1-26
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• 1996

This study was performed to estimate the effects of cultured bone cell inoculated on porous type hydroxyaptite for the regeneration of the artificial alveolar bone defect. In this experiment 3 beagle dogs were used, and each of them were divided into right and left mandible. Every surgical intervention were performed under the general anesthesia by using with intravenous injection of Pentobarbital sodium(30mg/Kg). To reduce the gingival bleeding during surgery, operative site was injected with Lidocaine hydrochloride(l:80,000 Epinephrine) as local anesthesia. After surgery experimental animal were feeded with soft dietl Mighty dog, Frisies Co., U.S.A.) for 1 weeks to avoid irritaion to soft tissue by food. 2 months before surgery both side of mandibular 1st premolar were extracted and bone chips from mandibular body were obtained from all animals. Bone cells were cultured from bone chips obtained from mandible with Dulbecco's Modified Essential Medium contained with 10% Fetal Bovine Serum under the conventional conditions. Porous type hydroxyapatite were immerse into the high concentrated cell suspension solution, and put 4 hours for attachin the cells on the surface of hydroxyapatite. Graft material were inserted on the artificial bone defect after 3 days of culture. Before insertion of cellinoculated graft material, scanning electronic microscopic observation were performed to confirm the attachment and spreading of cell on the hydroxyapatite surface. 3 artificial bone defects were made with bone trephine drill on the both side of mandible of the experimental animal. First defect was designed without insertion of graft material as negative control, second was filled with porous replamineform hydroxyapatite inoculated with cultured bone marrow cells as expermiental site, and third was filled with graft materials only as positive control. The size of every artificial bone defect was 3mm in diameter and 3mm in depth. After the every surgical intervention of animals, oral hygiene program were performed with 1.0% chlorhexidine digluconate. All of the animals were sacrificed at 2, 4, 6 weeks after surgery. For obtaining histological section, tissus were fixed in 10% Buffered formalin and decalcified with Planko - Rycho Solution for 72hr. Tissue embeding was performed in paraffin and cut parallel to the surface of mandibular body. Section in 8um thickness of tissue was done and stained with Hematoxylin - Eosin. All the specimens were observed under the light microscopy. The following results were obtained : 1. In the case of control site which has no graft material, less inflammatory cell infiltration and rapid new bone forming tendency were revealed compared with experimental groups. But bone surface were observed depression pattern on defect area because of soft tissue invasion into the artificial bone defect during the experimental period. 2. In the porous hydroxyapatite only group, inflammatory cell infiltration was prominet and dense connective tissue were encapsulated around grafted materials. osteoblastic activity in the early stage after surgery was low to compared with grafted with bone cells. 3. In the case of porous hydroxyapatite inoculated with bone cell, less inflammatory cell infiltration and rapid new bone formation activity was revealed than hydroxyapatite only group. Active new bone formation were observed in the early stage of control group. 4. The origin of new bone forming was revealed not from the center of defected area but from the surface of preexisting bony wall on every specimen. 5. In this experiment, osteoclastic cell was not found around grafted materials, and fibrovascular invasion into regions with no noticeable foreign body reaction. Conclusively, the cultured bone cell inoculated onto the porous hydroxyapatite may have an important role of regeneration of artificial bone defects of alveolar bone.

• Journal of Korea Water Resources Association
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• v.55 no.spc1
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• pp.1177-1185
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• 2022

The water and sewage system is an infrastructure that provides safe and clean water to people. In particular, since the water and sewage pipelines are buried underground, it is very difficult to detect system defects. For this reason, the diagnosis of pipelines is limited to post-defect detection, such as system diagnosis based on the images taken after taking pictures and videos with cameras and drones inside the pipelines. Therefore, real-time detection technology of pipelines is required. Recently, pipeline diagnosis technology using advanced equipment and artificial intelligence techniques is being developed, but AI-based defect detection technology requires a variety of learning data because the types and numbers of defect data affect the detection performance. Therefore, in this study, various defect scenarios are implemented using 3D printing model to improve the detection performance when detecting defects in pipelines. Afterwards, the collected images are performed to pre-processing such as classification according to the degree of risk and labeling of objects, and real-time defect detection is performed. The proposed technique can provide real-time feedback in the pipeline defect detection process, and it would be minimizing the possibility of missing diagnoses and improve the existing water and sewerage pipe diagnosis processing capability.

• Journal of Veterinary Clinics
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• v.31 no.1
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• pp.46-50
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• 2014

A 7-year-old spayed female Welsh corgi presented with a mass of the skull. The mass was diagnosed as multilobular bone tumor and surgically removed. To treat a large bone defect after the tumor removal, custom-made artificial bone fabricated by a 3-dimensional ink-jet printer was implanted in the defect. Follow-up computed tomography evaluation was performed for 4.3 years. The implant was well integrated with the skull and had covered the large bone defect during the follow-up period. Gradual degradation of the implant began 6 weeks after surgery. It provides an additional option for the treatment of large bone defect.