• Journal of the Korean Solar Energy Society
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• v.31 no.3
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• pp.17-22
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• 2011

Techniques for mismatch loss minimization to increase the PV system efficiency are under development recently. In this paper, a method to make diagnosis of PV module mismatch is presented, which uses a concept of operating point factor. The method is based on the fact that the ratio of the incremental conductance of a PV module to instantaneous conductance is 1 when the module is operating at its maximum power point. The variations of module voltage and current are taking place by the maximum power point tracker in the power conditioning units of PV system. The effectiveness of the method is verified through an application to a real PV system.

• Proceedings of the KIEE Conference
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• 2001.07c
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• pp.1727-1729
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• 2001

Partial discharge testing are rapidly becoming the most powerful tool to assess the condition of high voltage generator and motor stator windings. Recently, on-line monitoring scheme with trending technique is widely applied in insulation diagnosis. This paper describes the on-line partial discharge detecting techniques in the high voltage motor stator windings. Also, on-line monitoring system for an insulation diagnosis are proposed.

• Journal of the Korean Arthroscopy Society
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• v.15 no.2
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• pp.158-164
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• 2011

As the instruments as well as techniques for hip arthroscopy have developed, the interests and understandings of acetabular labral tear have also increased. As a consequence, the diagnosis itself was increased. However, it is still difficult to be diagnosed accurately in an ordinary clinic. In this brief review, the clinical and radiological characteristics and diagnostic implications of acetabular labral lesions were described to help the surgeon to make a right decision.

• Proceedings of the KSR Conference
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• 2010.06a
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• pp.546-548
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• 2010

This paper proposes a new baseline-free TR-based SHM method in which the time-reversal (TR) property of the guided Lamb waves is utilized. The new TR-based SHM method has two distinct features when compared with the other existing SHM techniques: (1) The measurement- based backward TR process is replaced by the computation-based process (2) In place of the comparison method most commonly used for SHM, the TOF information of the damage signal extracted from the reconstructed signal is utilized for the damage diagnosis. For the damage diagnosis, the imaging method is adopted to efficiently detect damage by representing the damage as an image. The proposed TR-based SHM technique is then validated through the damage diagnosis experiment for an aluminum plate with a damage at different locations.

• Journal of Computing Science and Engineering
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• v.8 no.2
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• pp.87-93
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• 2014

Coronary artery disease (CAD) is currently a prevalent disease from which many people suffer. Early detection and treatment could reduce the risk of heart attack. Currently, the golden standard for the diagnosis of CAD is angiography, which is an invasive procedure. In this article, we propose an algorithm that uses data mining techniques, a fuzzy expert system, and the imperialist competitive algorithm (ICA), to make CAD diagnosis by a non-invasive procedure. The ICA is used to adjust the fuzzy membership functions. The proposed method has been evaluated with the Cleveland and Hungarian datasets. The advantage of this method, compared with others, is the interpretability. The accuracy of the proposed method is 94.92% by 11 rules, and the average length of 4. To compare the colonial competitive algorithm with other metaheuristic algorithms, the proposed method has been implemented with the particle swarm optimization (PSO) algorithm. The results indicate that the colonial competition algorithm is more efficient than the PSO algorithm.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.63 no.11
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• pp.1545-1550
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• 2014

Fault detection and diagnosis (FDD) of photovoltaic (PV) power systems is one of significant techniques for reducing economic loss due to abnormality occurred in PV modules. This paper presents a new FDD method against PV power systems by using statistical comparison. This comparative approach includes deviation signals between the outputs of two neighboring PV modules. We first define a binary hypothesis testing under such deviation and make use of a generalized likelihood ratio testing (GLRT) theory to derive its FDD algorithm. Additionally, a recursive computational mechanism for our proposed FDD algorithm is presented for improving a computational effectiveness in practice. We carry out a real-time experiment to test reliability of the proposed FDD algorithm by utilizing a lab based PV test-bed system.

• Parasites, Hosts and Diseases
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• v.52 no.4
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• pp.345-353
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• 2014

Babesia gibsoni is an intraerythrocytic apicomplexan parasite that causes piroplasmosis in dogs. B. gibsoni infection is characterized clinically by fever, regenerative anemia, splenomegaly, and sometimes death. Since no vaccine is available, rapid and accurate diagnosis and prompt treatment of infected animals are required to control this disease. Over the past decade, several candidate molecules have been identified using biomolecular techniques in the authors' laboratory for the development of a serodiagnostic method, vaccine, and drug for B. gibsoni. This review article describes newly identified candidate molecules and their applications for diagnosis, vaccine production, and drug development of B. gibsoni.

• Proceedings of the Korean Society of Tribologists and Lubrication Engineers Conference
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• 2001.11a
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• pp.252-259
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• 2001

Integrated condition monitoring is required to monitor effectively the machine conditions since machine failures could not be monitored accurately by any single measurement parameter. Application of various condition monitoring techniques is therefore preferred in many cases in order to diagnosis the machine condition. However it inevitably requires lots of maintenance cost and sometimes it could be proved to over-maintenance unnecessarily. This could happen especially when one measurement parameter closely correlates to another. Therefore correlation analysis of various monitoring parameters has to be performed to improve the reliability of diagnosis. In this work, Pearson correlation coefficient was used to analyze the correlation between condition monitoring parameters of an over-loaded machine system where the vibration, wear and temperature were monitored simultaneously. The result showed that Pearson correlation coefficient could be regarded as a good measure for evaluating the availability of condition monitoring technology.

• KEPCO Journal on Electric Power and Energy
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• v.2 no.2
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• pp.293-298
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• 2016

Recently, interests for maintenance of transmission tower are increasing to extend life of structures and reduce maintenance cost. However, existing classical diagnosis method of corrosion deteriorated degree on the transmission tower steel members, visual inspection, has a problem that error often due to difference of inspector's individual knowledge and experience. In order to solve the problem, this study carried out to develop the corrosion deterioration inspection tool for transmission tower steel members. This tool is composed of camera equipment and computer-aided diagnosis system. We standardized the photographing method by camera equipment to obtain suitable pictures for image processing. Diagnosis system was designed to evaluate automatically degree of corrosion deterioration for member of transmission tower on the basis of the RGB color image processing techniques. It is anticipated that developed the corrosion deterioration inspection tool will be very helpful in decision of optimal maintenance time for transmission tower corrosion.

• Transactions on Electrical and Electronic Materials
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• v.7 no.6
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• pp.324-329
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• 2006

As the average usage period of transformers increases, it is becoming increasingly necessary to know the internal condition of transformers. It is therefore critically important to establish monitoring and diagnostic techniques that can perform transformer condition assessment. Frequency response analysis, generally known as FRA, is one of the technologies to diagnose transformers. Using case studies, this paper presents the effectiveness of FRA as measurements for detecting transformer failures. This paper introduces the fact that FRA waveforms have useful information about diagnosis of failure on core earths and winding shield, and that the condition outside transformers can affect frequency response characteristics.