• Proceedings of the KIEE Conference
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• 대한전기학회 2000년도 하계학술대회 논문집 C
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• pp.1903-1905
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• 2000

Power transformers have a tendency of ultra-high voltage capacity as power demand increases day after day KEPCO also will have plan to supply transmission power from 345KV to 765KV in the early of 2000. Therefore, the fault by insulation destruction gives rise to large area of power failure in huge capacity transformers. On-line predictive diagnostics is very important in power transformers because of economic loss and its spreading effect. This study presents the algorithm for transformer oil analysis used KEPCO code, IEC code, gas pattern method and Dornenburg & Roger Ratio method. We also describe the MMI display of expert system programmed by Element Expert Tool(Neuron Data Inc.).

• The Journal of the Korea institute of electronic communication sciences
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• 제10권2호
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• pp.195-202
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• 2015

Rotating equipment seldom fails without notice, so breakdowns can usually be predicted and avoided by watching for signs of failure. In this paper, We study case for rotary machine with a breakdown analysis. Also We analyze the solution of the safety and the future breakdown of the each rotary machine through vibration analysis using measurement data. The implementation of the measurement and the test results are discussed. The result with suggested method showed netter stable Condition Monitoring & Diagnostics.

• Proceedings of the Korean Society of Propulsion Engineers Conference
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• 한국추진공학회 2008년도 제31회 추계학술대회논문집
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• pp.388-392
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• 2008

Research of methods for preventing accidents and minimizing losses during the liquid rocket engine (LRE) test and its exploration is of current importance. In this paper the steps of progress to LRE accidents are defined, and methods for preventing LRE accidents and minimizing losses from accidents are considered. The suggested methods in this paper can be applied to LRE test and exploration for protecting engine system from emergency situation.

• Journal of Drive and Control
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• 제20권4호
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• pp.54-63
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• 2023

High and intermittent loading cycles induce fatigue damage to transmission components, resulting in premature gearbox failure. To identify gearbox defects, numerous vibration-based diagnostics techniques, using several artificial intelligence (AI) algorithms, have recently been presented. In this paper, an optimized deep belief network (DBN) model for gearbox problem diagnosis was designed based on time-frequency visual pattern identification. To optimize the hyperparameters of the model, a particle swarm optimization (PSO) approach was integrated into the DBN. The proposed model was tested on two gearbox datasets: a wind turbine gearbox and an experimental gearbox. The optimized DBN model demonstrated strong and robust performance in classification accuracy. In addition, the accuracy of the generated datasets was compared using traditional ML and DL algorithms. Furthermore, the proposed model was evaluated on different partitions of the dataset. The results showed that, even with a small amount of sample data, the optimized DBN model achieved high accuracy in diagnosis.

• Korean Journal of Veterinary Research
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• 제57권1호
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• pp.31-36
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• 2017

Japanese encephalitis (JE) is an important zoonosis caused by the mosquito-transmitted JE virus (JEV), which is a causative agent of reproductive failure in pregnant sows. Detection of JEV antibodies in swine is performed by hemagglutination inhibition (HI), virus neutralization (VN), and the plaque reduction neutralization test (PRNT). The most stringent PRNT is the 90% endpoint PRNT ($PRNT_{90}$). These conventional assays are difficult to carry out in diagnostic laboratories with insufficient instruments or cell culture systems. An alternative assay that is easily conducted and time efficient is required. In this study, we improved the indirect enzyme-linked immunosorbent assay (I-ELISA) with clarified antigen for the detection of JEV antibodies. The I-ELISA results obtained from 175 swine serum samples were compared with HI, VN, and $PRNT_{90}$ results. The sensitivity of I-ELISA was 91.8%, 95.0%, and 94.7% compared with HI, VN, and $PRNT_{90}$ results, respectively. The specificity of I-ELISA was 92.2%, 94.7%, and 94.7% compared with HI, VN, and $PRNT_{90}$ results, respectively. Moreover, the I-ELISA results were significantly correlated with the HI (r = 0.93), VN (r = 0.95), and $PRNT_{90}$ (r = 0.92) results. These results suggest that the improved I-ELISA is useful for serosurveillance of JEV in swine.

• Journal of Mechanical Science and Technology
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• 제18권9호
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• pp.1537-1548
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• 2004

This paper presents a novel diagnostic technique for monitoring the system conditions and detecting failure modes and precursors based on wavelet-packet analysis of external noise/vibration measurements. The capability is based on extracting relevant features of noise/vibration data that best discriminate systems with different noise/vibration signatures by analyzing external measurements of noise/vibration in the time-frequency domain. By virtue of their localized nature both in time and frequency, the identified features help to reveal faults at the level of components in a mechanical system in addition to the existence of certain faults. A prima-facie case is made via application of the proposed approach to fault detection in scroll and rotary compressors, although the methods and algorithms are very general in nature. The proposed technique has successfully identified the existence of specific faults in the scroll and rotary compressors. In addition, its capability of tracking the severity of specific faults in the rotary compressors indicates that the technique has a potential to be used as a prognostic tool.

• Journal of Korean Institute of Industrial Engineers
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• 제27권1호
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• pp.61-68
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• 2001

A rotor system is composed of a rotating shaft with supporting bearings. The rotor system is widely used in every rotating machinery such as the turbine generator and the high precision machine tools. A negligible error or malfunction in the rotor, however, can cause a catastrophic failure in the system then result in the environmental and economic disasters. A diagnosis of the rotor system is important in preventing these kinds of failures and disasters. Up to now, many researchers have devoted in the development of diagnosing tools for the system. The basic principles behind the tools are to retrieve the data through the sensors for a specific state of the system and then to identify the specific state through the heuristic methods such as neural network, fuzzy logic, and decision matrix. The proper usage of the heuristic methods will enhance the performance of the diagnostic procedure when together used with the statistical signal processing. In this paper, the methodologies in using the above 3 heuristic methods for the diagnostics of the rotor system are established and also tested and validated for the data retrieved from the rolling element bearing and journal bearing supported system.

• Proceedings of the KIEE Conference
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• 대한전기학회 1998년도 추계학술대회 논문집 학회본부 C
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• pp.941-943
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• 1998

Exploitation of equipment with cross linked polyethylene (XLPE) insulation requires its condition monitoring and diagnostic. Traditionally diagnostics of insulation is carried out by means of partial discharge detection. Many researchers have developed a lot of methods to identify the defect by the PD form. However, such identification of a defect, for example, void, inclusion or treeing, does not say about its danger from a point of view of full insulation gap breakdown and insulation construction failure. The information about the form and size of formed upon high voltage treeing is necessary for prediction of the remained resource of XLPE insulation. For this purpose we carry out experimental research for determination of the dependencies between PD characteristics in XLPE upon time and three dimension PD patterns of corresponding treeing. The investigations were carried out by means of electrical measurement of PD current and simultaneous optical recording of treeing image. Test results show that the PD patterns can be applied for detecting tree growth well.

• Journal of the Korean Society for Precision Engineering
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• 제32권5호
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• pp.447-454
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• 2015

Design and application of hardware-in-the-loop simulation (HILS) for design of CNC-controlled machine tool feed drives is discussed. The CNC machine tool is a complex mechatronics system where the complexity results from the software-based controller composed of a variety of functionalities and advanced control algorithms. Therefore, using a real CNC controller in the control simulation has merits considering the efforts and accuracy of the simulation modeling. In this paper challenges in HILS for a CNC controlled feed drive, such as minimization of time delay and transmission error that are caused by discretization of the feed drive model, is elaborated. Using an experimental HILS setup of a machine tool feed drive applications in controller gain selection and CNC diagnostics are presented.

• Proceedings of the Korea Society for Industrial Systems Conference
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• 한국산업정보학회 2008년도 추계 공동 국제학술대회
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• pp.96-103
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• 2008

The information systems audit is an proactive action to find out the predicted issues on proceeding the business beforehand, to make out whether the information systems satisfies the user's demand or not and to check up the result of the project with complementing the capabilities of self-diagnostics for the complicated and advanced information system. However, the results of the audited project are apt to be regarded as a failure in a case that an opinion of the audit area evaluation is described as 'insufficient' or 'negative' in the audit report that is submitted as the result of the audit. It makes a lot of arguments among the board of audit, the institution ordering the audit and the auditor. In this study, we made an attempt to finding out the factors affecting the audit area evaluation and verifying them objectively. A study model and hypothesis including the improvement type of the recommended subject to be improved, the importance, the audit time, the business scale of the audited object and the auditing company as a factor variable were established and the hypothesis was verified by analyzing the correlation between the factor variables and the audit area evaluation.