• Journal of the Korean Society of Manufacturing Process Engineers
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• v.20 no.9
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• pp.28-34
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• 2021

The Fourth Industrial Revolution has led to the development of drones for commercial and private applications. Therefore, the malfunction of drones has become a prominent problem. Failure mode and effect analysis was used in this study to analyze the primary cause of drone failure, and blade breakage was observed to have the highest frequency of failure. This was tested using a vibration sensor placed on drones along the breakage length of the blades. The data exhibited a significant increase in vibration within the drone body for blade fracture length. Principal component analysis was used to reduce the data dimension and classify the state with machine learning algorithms such as support vector machine, k-nearest neighbor, Gaussian naive Bayes, and random forest. The performance of machine learning was higher than 0.95 for the four algorithms in terms of accuracy, precision, recall, and f1-score. A follow-up study on failure prediction will be conducted based on the results of fault diagnosis.

• Journal of the Korean Society of Safety
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• v.34 no.1
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• pp.14-20
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• 2019

This paper presents a safety assessment based approach for the safe operation for PCS(Power Conditioning System) of photovoltaic and energy storage systems, applying FTA. The approach established top events as power outage and a failure likely to cause the largest damage among the potential risks of PCS. Then the Minimal Cut Set (MCS) and the importance of basic events were analyzed for implementing risk assessment. To cope with the objects, the components and their functions of PCS were categorized. To calculate the MCS frequency based on IEEE J Photovolt 2013, IEEE Std. 493-2007 and RAC (EPRD, NPRD), the failure rate and failure mode were produced regarding the basic events. In order to analyze the top event of failure and power outage, it was assumed that failures occurred in DC breaker, AC breaker, SMPS, DC filter, Inverter, CT, PT, DSP board, HMI, AC reactor, MC and EMI filter and Fault Tree was drawn. It is expected that the MCS and the importance of basic event resulting from this study will help find and remove the causes of failure and power outage in PCS for efficient safety management.

• The Transactions of the Korean Institute of Power Electronics
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• v.27 no.5
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• pp.410-416
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• 2022

A grid-connected inverter with critical loads uses mode transfer control to supply stable voltage to the load. An islanding detection method should also be used to quickly detect the grid fault and disconnect the inverter from the grid. However using the existing islanding detection method to detect islanding is difficult due to the small fluctuation of the voltage and frequency of the point of common coupling. This study proposes a reactive power P&O islanding detection method by using the positive feedback technique. The proposed method always injects a small variation of reactive power. When a grid fault occurs, the injected reactive power accelerates the reactive power injection reference. As a result, the reactive power reference value and the sensed reactive power become mismatched, and islanding is detected. Reducing the amount of real-time injected reactive power results in high efficiency and power factor. The simulation and experimental results of a 3 kW single-phase inverter are provided to verify the proposed islanding detection method.

• Proceedings of the Mineralogical Society of Korea Conference
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• 2000.05a
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• pp.24-24
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• 2000

We studied about petrological characteristics of the Bangeujin granite belongs to porphyritic biotite granite, petrogenesis of the enclaves in the granite and contact metamorphism of the sedimentary rock around the granite. The enclaves in the granite are concentrated in the eastern part of the Mipo fault but in the western part, these are rare. The enclaves can be divided into three types according to the petrographical characteristics. These three types are: (1) enclaves having few phenocrysts and fine grained igneous texture and ellipsoid is predominant; (2) enclaves similar In petrographical characteristics and having many phenocrysts considered as being originated from the granitic host rock; and (3) enclaves corresponding to granite in mode composition, having large phenocrysts and of which the matrix is corresponding to fine granular. First two types are correspond to mafic micro granular enclaves and the third is corresponds to felsic microgranular enclaves. In addition, the felsic microgranular enclaves capture the mafic microgranular enclaves. The fact that the compositions of biotite and plagioclase in the enclaves are nearly identical with those of biotite and plagioclase in the granitic host rock is considered as the results of supporting magma mingling. The major elements show well the linear variations as the SiOz$.$ content increases. The rare earth elements content decrease with increasing SiOz content, interpreted as the results of magma mingling. Therefore, we can conclude that the Bangeujin granite captured the felsic microgranular enclaves formed by collapse of early chilled margin during the crystallization and there was magma mingling by the injection of the mafic magma after that time. In addition, these aspects are predominant in the eastern part of the Mipo fault is considered as related to the fault movement.vement.

• Proceedings of the KSEEG Conference
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• 2003.04a
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• pp.7-14
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• 2003

The precious-meta] mineralization of epithermal type in the Korean Peninsula, which is spread over a broader range of ca. 110 to 60 Ma with a major population between 90 and 70 Ma, mainly occurred along the NE-trending major strike-slip fault systems (i.e., the Gongju and Gwangju ones) that commonly include volcano-tectonic depressions and calderas. The occurrence of epithermal mineralization during Late Cretaceous clearly indicates that the geologic setting of the Korean Peninsula changed to the favorable depth of ore formation with very shallow-crustal environments (〈1.0 kb) accompanied with gold-silver (-base-meta]) mineralization. Epithermal gold-silver deposits in Korea are primarily distinguished as sediment-dominant and volcanic-dominant basins by using criteria of varying alteration, ore and gangue mineralogy deposited by the interaction of different ore-forming fluids with host rocks and meteoric waters. These differences between the central and southern portions are causally linked to the tectonic evolution of the Peninsula during the Cretaceous time. In the Early Cretaceous, the sinistral strike-slip movements due to the oblique subduction of the Izanagi Plate resulted in the Gongju and Gwangju fault systems in the central portion of the Korean Peninsula, which was accompanied with a number of sediment-dominant basins formed along these faults. During the Late Cretaceous, the mode of convergence of the Izanagi Plate changed to northwesteward so that orthogonal convergence occurred with a calc-alkaline volcanism. As results, volcanic-dominant basins were developed in the southern portion of the Peninsula, accompanied with volcano-tectonic depressions and caldera-related fractures. The magmatism and related fractures during Late Cretaceous may play an important role in the formation of geothermal systems. Thus, such fault zones may be favorable environments for veining emplacement that is closely related to the precious-metal mineralization of epithermal type in the Korean Peninsula.

• Journal of the Korean Society of Propulsion Engineers
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• v.25 no.2
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• pp.88-97
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• 2021

The controller of the gas turbine engine is a component that needs to be developed for the development of the gas turbine engine because it is impossible to get the technology transferred from the engine manufacturer due to the import and export regulation. As a part of the engine control logic research, the Korea Aerospace Research Institute conducted a failure diagnostic research using a small gas turbine engine. Before simulating the engine fault, the ground test was performed to analyze normal behavior and performance of engine. Afterwards, the control logic analysis test equipment was established to simulate various engine fault. It is intended to provide background knowledge to engine control logic research for various engine failure conditions.

• Journal of the Computational Structural Engineering Institute of Korea
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• v.30 no.2
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• pp.169-177
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• 2017

In this paper, classification of spall and crack faults of gear teeth is studied by applying the ensemble empirical mode decomposition(EEMD) for the gear transmission error(TE). Finite element models of the gears with the two faults are built, and TE is obtained by simulation of the gears under loaded contact. EEMD is applied to the residuals of the TE which are the difference between the normal and faulty signal. From the result, the difference of spall and crack faults are clearly identified by the intrinsic mode functions(IMF). A simple test bed is installed to illustrate the approach, which consists of motor, brake and a pair of spur gears. Two gears are employed to obtain the TE for the normal, spalled, and cracked gears, and the type of the faults are separated by the same EEMD application process. In order to quantify the results, crest factors are applied to each IMF. Characteristics of spall and crack are well represented by the crest factors of the first and the third IMF, which are used as the feature signals. The classification is carried out using the Bayes decision theory using the feature signals acquired through the experiments.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.43 no.5
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• pp.449-455
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• 2015

Built-In-Test(hereafter: BIT) is necessary functionality for aircraft flight safety and it requires a high failure detection capacity of more than 95 % in the case of avionics equipment. The BIT coverage analysis is needed to make sure that BIT meets its fault diagnosis capability. FMECA is used a lot of for the BIT coverage analysis. However, in this paper, the BIT coverage analysis based on electronic components is introduced to minimize the analytical error. Further, by applying the failure mode of the electronic components and excluding electronic components that do not affect flight safety, the BIT coverage analysis can be more accurate. Finally, BIT demo was performed and it was confirmed that the performance of the actual BIT matches the analysis of BIT performance.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.19 no.5
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• pp.611-617
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• 2018

The application of health monitoring, including a fault detection technique, is needed to secure the structural safety of large structures. A 2-step crack identification method for detecting the crack location and size of the beam structure is presented. First, a crack occurrence region was estimated using the modified Laplacian operator for the strain mode shape obtained from the distributed local strain data. The crack location and size were then identified based on the natural frequencies obtained from the acceleration data and the neural network technique for the pre-estimated crack occurrence region. The natural frequencies of a cracked beam were calculated based on an equivalent bending stiffness induced by the energy method, and used to generate the training patterns of the neural network. An experimental study was carried out on an aluminum cantilever beam to verify the present method for crack identification. Cracks were produced on the beam, and free vibration tests were performed. A crack occurrence region was estimated using the modified Laplacian operator for the strain mode shape, and the crack location and size were assessed using the natural frequencies and neural network technique. The identified crack occurrence region agrees well with the exact one, and the accuracy of the estimation results for the crack location and size could be enhanced considerably for 3 damage cases. The presented method could be applied effectively to the structural health monitoring of large structures.

• Transactions of the Korean Society for Noise and Vibration Engineering
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• v.27 no.2
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• pp.189-194
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• 2017

An compressor that is combined with the rotor and pneumatic technology has been researching for the performance of pressure. However, the control of operations, an accurate diagnosis and the maintenance of compressor system are limited though the simple structure of compressor and compression are advantaged to reduce the energy. In this paper, the characteristic of the compressor operating under the normal or abnormal condition is realized. and the efficient diagnosis method is proposed through feature based analysis. Also, by using the GA (genetic algorithm) and SVM (support vector machine) of machine learning, the performance of feature analysis is conducted. Different misalignment mode of learning data for compressor is evaluated using the fault simulator. Therefore, feature based analysis is conducted considering misalignment mode of the compressor and the possibility of a diagnosis of misalignment is evaluated.