• Journal of Electrical Engineering and Technology
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• 제11권6호
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• pp.1729-1734
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• 2016

The surface inspection of a steel billet is a common practice in the steel manufacturing process prior to hot rolling to produce steel wire for tire cord. This billet surface inspection is an important process because flaws on the surface may cause major failures during the product manufacturing phase. This paper presents a computer simulation based on a finite element method for a magnetic flaw detector with a function of the current intensity, the number of coil turns, and the billet proceeding speed during the production phase based on the typical condition of conventional apparatus. Based on the simulation result, the magnitude of the electromagnetic field on the surface diminished with distance from the electromagnet. In addition, the increased current intensity and the increased number of coil turns actually induced a stronger electromagnetic field on the billet surface. On the other hand, the proceeding speed of a billet in its production line had no significant effects. The result in this study may assist to reduce trial and error and to minimize the opportunity costs during the optimization process by applying the findings of this study into the operation condition in the steel billet production line.

• 센서학회지
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• 제3권1호
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• pp.32-39
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• 1994

알코올증기를 검출하기 위하여 접촉연소식 센서를 제작하고 그 특성을 조사하였다. 검지용 백금코일의 저항을 $2{\Omega}$으로 하였을 때, 적정인가전력은 메탄올에 대해서 300 mW, 에탄올에 대해서 350 mW에서 400 mW의 범위에 있었다. 검지소자는 백금 또는 팔라듐을 ${\gamma}-Al_{2}O_{3}$ bead위에 함침 도포하였으며, 보상소자용으로는 $Co_{3}O_{4}$, $Fe_{2}O_{3}$ 등의 전이금속 산화물을 사용하였다.

• Steel and Composite Structures
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• 제14권4호
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• pp.367-377
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• 2013

Damage in structures often leads to failure. Thus it is very important to monitor structures for the occurrence of damage. When damage happens in a structure the consequence is a change in its modal parameters such as natural frequencies and mode shapes. Artificial Neural Networks (ANNs) are inspired by human biological neurons and have been applied for damage identification with varied success. Natural frequencies of a structure have a strong effect on damage and are applied as effective input parameters used to train the ANN in this study. The applicability of ANNs as a powerful tool for predicting the severity of damage in a model steel girder bridge is examined in this study. The data required for the ANNs which are in the form of natural frequencies were obtained from numerical modal analysis. By incorporating the training data, ANNs are capable of producing outputs in terms of damage severity using the first five natural frequencies. It has been demonstrated that an ANN trained only with natural frequency data can determine the severity of damage with a 6.8% error. The results shows that ANNs trained with numerically obtained samples have a strong potential for structural damage identification.

• 한국공간구조학회:학술대회논문집
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• 한국공간구조학회 2008년도 춘계 학술발표회 논문집
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• pp.179-183
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• 2008

콘크리트에서의 손상 검증법은 비파괴 시험법을 주로 이용한다. 이러한 비파괴시험법은 다양한 센서를 이용하지만, 대부분의 손상을 검사하는 방법은 육안으로 확인한다. 비파괴 시험법에서 가속도계를 이용하여 철근 콘크리트 부재 내부의 불규칙한 균열 손상을 측정하기에는 철근의 방향성과 경계조건으로 어려움이 많다. 본 연구에서는 3축 가속도센서를 이용하고 탄성파를 가진하여, 콘크리트 부재 내부에 철근의 배치방향에 따른 영향 검토와 강도가 저하된 부재의 손상을 검토하기 위한 기초적 연구이다.

• Journal of Advanced Marine Engineering and Technology
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• 제31권6호
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• pp.791-796
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• 2007

When 2 sets of PID controllers are coupled directly each other to configure a closed control loop on behalf of coupling a controller and a plant. the behaviors or this exclusive loop system are expected to be unique in inherent system responses. If its properties be disclosed and generalized well in advance, it is possible for us to use the results for the purpose of fault detection and performance monitoring between control stations from the stage of system design. particularly in such cases as cascade control systems. In this paper. general properties of the proposed system are analyzed firstly to check whether it is controllable and how its steady responses would be. To simplify calculation, the analysis has been performed based on the transfer equation derived from a modelled case which consists of 2 PI controllers and signal converters between them. including time delay element and first-lag element to consider the situation of signal transmission. The results acquired from simulation are suggested to show how it works actually.

• Structural Engineering and Mechanics
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• 제46권5호
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• pp.615-627
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• 2013

One of the most common defects in reinforced concrete bridge decks is corrosion of steel reinforcing bars. This invisible defect reduces the deck stiffness and affects the bridge's serviceability. Regular monitoring of the bridge is required to detect and control this type of damage and in turn, minimize repair costs. Because the corrosion is hidden within the deck, this type of damage cannot be easily detected by visual inspection and therefore, an alternative damage detection technique is required. This research develops a non-destructive method for detecting reinforcing bar corrosion. Experimental modal analysis, as a non-destructive testing technique, and finite element (FE) model updating are used in this method. The location and size of corrosion in the reinforcing bars is predicted by creating a finite element model of bridge deck and updating the model characteristics to match the experimental results. The practicality and applicability of the proposed method were evaluated by applying the new technique to a two spans bridge for monitoring steel bar corrosion. It was shown that the proposed method can predict the location and size of reinforcing bars corrosion with reasonable accuracy.

• Computers and Concrete
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• 제20권5호
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• pp.583-593
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• 2017

Applications of fibre-reinforced polymer (FRP) composites for retrofitting, strengthening and repairing concrete structures have been expanded dramatically in the last decade. FRPs have high specific strength and stiffness compared to conventional construction materials, e.g., steel. Ease of preparation and installation, resistance to corrosion, versatile fabrication and adjustable mechanical properties are other advantages of the FRPs. However, there are major concerns about long-term performance, serviceability and durability of FRP applications in concrete structures. Therefore, structural health monitoring (SHM) and damage detection in FRP-retrofitted concrete structures need to be implemented. This paper presents a study on investigating the application of Rayleigh wave for detecting debonding defect in FRP-retrofitted concrete structures. A time-of-flight (ToF) method is proposed to determine the location of a debonding between the FRP and concrete using Rayleigh wave. A series of numerical case studies are carried out to demonstrate the capability of the proposed debonding detection method. In the numerical case studies, a three-dimensional (3D) finite element (FE) model is developed to simulate the Rayleigh wave propagation and scattering at the debonding in the FRP-retrofitted concrete structure. Absorbing layers are employed in the 3D FE model to reduce computational cost in simulating the practical size of the FRP-retrofitted structure. Different debonding sizes and locations are considered in the case studies. The results show that the proposed ToF method is able to accurately determine the location of the debonding in the FRP-retrofitted concrete structure.

• 대한의생명과학회지
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• 제13권4호
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• pp.319-324
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• 2007

One-tube nested polymerase chain reaction (PCR) was evaluated for its efficacy in detecting Mycobacterium leprae in biopsy samples from leprosy patients. Primers were derived from the M leprae-specific element (RLEP) sequences which yield a 230 bp fragment. The specificity and the sensitivity of the one-tube nested PCR were compared with those of single PCR for detecting M leprae. The results showed that the one-tube nested PCR was about 100 times more sensitive than that of the single indicating the one-tube nested primer sets developed in this study can be an effective screening tool for the detection of M leprae in clinical diagnostic laboratories.

• Nuclear Engineering and Technology
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• 제52권10호
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• pp.2262-2273
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• 2020

Digital twin technology can provide significant value for the prognostics and health management (PHM) of critical plant components by improving insight into system design and operating conditions. Digital twinning of systems can be utilized for anomaly detection, diagnosis and the estimation of the system's remaining useful life in order to optimize operations and maintenance processes in a nuclear plant. In this regard, a conceptual framework for the application of digital twin technology for the prognosis of Control Element Drive Mechanism (CEDM), and a data-driven approach to anomaly detection using coil current profile are presented in this study. Health management of plant components can capitalize on the data and signals that are already recorded as part of the monitored parameters of the plant's instrumentation and control systems. This work is focused on the development of machine learning algorithm and workflow for the analysis of the CEDM using the recorded coil current data. The workflow involves features extraction from the coil-current profile and consequently performing both clustering and classification algorithms. This approach provides an opportunity for health monitoring in support of condition-based predictive maintenance optimization and in the development of the CEDM digital twin model for improved plant safety and availability.

• 전기학회논문지
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• 제58권5호
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• pp.929-935
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• 2009

As modem industrialized society progresses, the demand for electric power is increasing rapidly. The electric power system is getting amazingly bigger and complicated, which can easily induce serious troubles from the potential of large fault problems and/or system failure. The monitoring and diagnosis of the electric machine for the fault detection and protection has been important part in the electric power system. Most faults in the generator appear in the winding. This paper presents the air-gap magnetic flux characteristic of a small-scale 2-pole synchronous generator according to the faults in the field winding to protect the generator from the fault. The magnetic flux patterns in air-gap of a generator under various fault conditions as well as a normal state are simulated by using finite element method. These results are successfully applied to the detection and diagnosis of the short-circuit condition in rotor windings of a high capacitor generator.