• Composites Research
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• v.28 no.6
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• pp.348-355
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• 2015

NDT (Non Destructive Test) of the adhesive joints is very important because their strengths have greatly affected by the worker's skill and environmental condition. Recently, the electric impedance method in which 1-2 wt% CNT was dispersed in the adhesive and the electric resistance of the adhesive joint was measured was suggested for the defect detection of the adhesive joint. The uniform dispersion of CNT in the electric impedance method is very important to make a constant electric resistance of the adhesive joint and the accuracy of defect detection depends on the uniform dispersion. In this paper, the adhesive joints in which CNT was dispersed in the adhesive by the four dispersion methods were made and their electric resistance were measured. The pre-process and evaporation process of CNT using the ultrasonic method and agitation method was used and the effective dispersion method was suggested. Also, the criteria to evaluate the dispersivity was proposed.

• Journal of the Korean Recycled Construction Resources Institute
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• v.8 no.3
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• pp.372-378
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• 2020

In this study, an experiment was conducted on the development and performance of self-propelled vehicles to repair defects in concrete sewage pipes. The self-propelled vehicle for a non-excavation repair for the sewage pipe defects was developed in consideration of the performance of the driving system, the feasibility of the repair unit, and the transportation of repair materials. In order to evaluate the performance of the developed self-propelled vehicle, a repair test was performed by simulating a defect at a connection between the main pipe and extruded one. The main sewage pipe was meade of concrete and its diameter was 500mm. Thereafter, watertightness performance was evaluated on the leakage at the repaired part. For watertightness performance, both ends of concrete sewage pipe and connected one was inserted by plugs, and then water was injected. The amount of leakage water measurement was 0.07L/㎡, indicating a value less than 0.2L/㎡ of the allowable leakage amount. Therefore, test results indicated that the self-propelled vehicle developed in this study exhibited excellent maintenance performance for repairing the sewage pipes.

• Smart Structures and Systems
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• v.22 no.4
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• pp.481-493
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• 2018

Ultrasonic guided waves have attracted increasing attention for non-destructive testing (NDT) and structural health monitoring (SHM) of bridge cables. They offer advantages like single measurement, wide coverage of acoustical field, and long-range propagation capability. To design defect detection systems, it is essential to understand how guided waves propagate in cables and how to select the optimal excitation frequency and mode. However, certain cable characteristics such as multiple wires, anchorage, and polyethylene (PE) sheath increase the complexity in analyzing the guided wave propagation. In this study, guided wave modes for multi-wire bridge cables are identified by using a semi-analytical finite element (SAFE) technique to obtain relevant dispersion curves. Numerical results indicated that the number of guided wave modes increases, the length of the flat region with a low frequency of L(0,1) mode becomes shorter, and the cutoff frequency for high order longitudinal wave modes becomes lower, as the number of steel wires in a cable increases. These findings were used in design of transducers for defect detection and selection of the optimal wave mode and frequency for subsequent experiments. A magnetostrictive transducer system was used to excite and detect the guided waves. The applicability of the proposed approach for detecting and locating wire breakages was demonstrated for a cable with 37 wires. The present ultrasonic guided wave method has been found to be very responsive to the number of brokenwires and is thus capable of detecting defects with varying sizes.

• Journal of the Korea Convergence Society
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• v.9 no.3
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• pp.53-59
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• 2018

In this paper, we propose a sequence mining based manufacturing process using a decision model in cognitive factory. The proposed model is a method to increase the production efficiency by applying the sequence mining decision model in a small scale production process. The data appearing in the production process is composed of the input variables. And the output variable is composed the production rate and the defect rate per hour. We use the GSP algorithm and the REPTree algorithm to generate rules and models using the variables with high significance level through t-test. As a result, the defect rate are improved by 0.38% and the average hourly production rate was increased by 1.89. This has a meaning results for improving the production efficiency through data mining analysis in the small scale production of the cognitive factory.

• International Journal of Naval Architecture and Ocean Engineering
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• v.10 no.2
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• pp.153-169
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• 2018

A submarine has a pressure hull that can withstand high hydraulic pressure and therefore, requires the use of highly advanced shipbuilding technology. When producing a pressure hull, periodic inspection, repair, and maintenance are conducted to maintain its soundness. Of the maintenance methods, Non-Destructive Testing (NDT) is the most effective, because it does not damage the target but sustains its original form and function while inspecting internal and external defects. The NDT process to detect defects in the welded parts of the submarine is applied through Magnetic particle Testing (MT) to detect surface defects and Ultrasonic Testing (UT) and Radiography Testing (RT) to detect internal defects. In comparison with RT, UT encounters difficulties in distinguishing the types of defects, can yield different results depending on the skills of the inspector, and stores no inspection record. At the same time, the use of RT gives rise to issues related to worker safety due to radiation exposure. RT is also difficult to apply from the perspectives of the manufacturing of the submarine and economic feasibility. Therefore, in this study, the Phased Array Ultrasonic Testing (PAUT) method was applied to propose an inspection method that can address the above disadvantages by designing a probe to enhance the precision of detection of hull defects and the reliability of calculations of defect size.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.25 no.9
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• pp.1144-1151
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• 2021

The pressing process is a compression process in which a product is made by applying force to a heated or unheated material to transform it into the desired shape. Due to the characteristics of press equipment that produces products through continuous compression for a short time, product defects occur continuously, and systems for solving these problems are being developed using various technologies. This paper proposes a real-time defect detection system based on an artificial intelligence algorithm that detects defects. By attaching various sensors to the press device, the relationship between equipment status and defects is defined and collected based on a big data platform. By developing an artificial intelligence algorithm based on the collected data and implementing the developed algorithm using an embedded board, we will show the practicality of the system by applying it to the actual field.

• Journal of the Korean Institute of Electrical and Electronic Material Engineers
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• v.32 no.4
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• pp.276-280
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• 2019

In this study, we investigated the crystal defects and grain boundary properties in a ZZCCC ($ZnO-Zn_2BiVO_6-Co_3O_4-Cr_2O_3-CaCO_3$) varistor, with the liquid-phase sintering aid $Zn_2BiVO_6$ developed by our laboratory. The ZZCCC varistor sintered at $1,200^{\circ}C$ exhibited excellent nonlinear current-voltage characteristics (${\alpha}=63$), with oxygen vacancy ($V_o^*$ ; 0.35 eV) as a main defect, and an apparent activation energy of 1.1 eV with an electrically single grain boundary. Therefore, among the various additives to improve the electrical properties of ZnO varistors, if $Zn_2BiVO_6$ is used as a liquid phase sintering aid, it will be ideal to use Co for the oxygen vacancy and Ca for the electrically single grain boundary. This will allow the good properties of ZnO varistors to be maintained up to high sintering temperatures.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.25 no.3
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• pp.471-477
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• 2021

In the field of display, a smart factory means more efficient display manufacturing using AI/BIG DATA technology not only for job automation, but also for existing process management, moving facilities, process abnormalities, and defect classification. In the past, when defects appeared in the display manufacturing process, the classification of defects and coping with process abnormalities were different, a lot of time was consumed for this. However, in the field of display manufacturing, advanced process equipment must be used, and it can be said that the competitiveness of the display manufacturing industry is to quickly identify the cause of defects and increase the yield. In this paper, we will summarize the cases in which smart factory AI/BIG DATA technology is applied to domestic display manufacturing, and analyze what advantages can be derived compared to existing methods. This information can be used as prior knowledge for improved smart factory development in the field of display manufacturing using AI/BIG DATA.

• Transactions of the Korean Society of Mechanical Engineers B
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• v.38 no.8
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• pp.657-663
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• 2014

Since 2007, the defect confirmation test for vehicles using PEMS has been enforced in USA. This test can measure emissions from on-street vehicles using a device mounted on a car. Europe has confirmed its plan for introducing this test from EURO6, 2013. Thus, the Korean government is also under pressure to adopt this method that reflects the real-world driving conditions using PEMS, considering the emission controls for domestic heavy-duty vehicles. To provide various utilizations of the PEM, this emission test has been developed in accordance with the type of driving road, DPF, ISG, and air conditioner. This research aims to provide the fundamental materials for implementing defect confirmation tests for commercial vehicles, which are appropriate for domestic emission control situations, after studying the defect confirmation test methods for heavy-duty vehicles using PEMS.

• Nuclear Engineering and Technology
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• v.38 no.3
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• pp.293-300
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• 2006

A liquid metal reactor (LMR) operated at high temperatures is subjected to both cyclic mechanical loading and thermal loading; thus, creep-fatigue is a major concern to be addressed with regard to maintaining structural integrity. The Korea Advanced Liquid Metal Reactor (KALIMER), which has a normal operating temperature of $545^{\circ}C$ and a total service life time of 60 years, is composed of various cylindrical structures, such as the reactor vessel and the reactor baffle. This study focuses on the creepfatigue crack initiation for a cylindrical Y-junction structure made of 316 stainless steel (SS), which is subjected to cyclic axial tensile loading and thermal loading at a high-temperature hold time of $545^{\circ}C$. The evaluation of the considered creep-fatigue crack initiation was carried out utilizing the ${\sigma}_d$ approach of the RCC-MR A16 guide, which is the high-temperature defect assessment procedure. This procedure is based on the total accumulated strain during the service time. To confirm the evaluated result, a high-temperature creep-fatigue structural test was performed. The test model had a circumferential through wall defect at the center of the model. The defect front of the test model was investigated after the $100^{th}$ cycle of the testing by utilizing a metallurgical inspection technique with an optical microscope, after which the test result was compared with the evaluation result. This study shows how creep-fatigue crack initiation for a high-temperature structure can be predicted with conservatism per the RCC-MR A16 guide.