• Tribology and Lubricants
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• v.38 no.4
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• pp.143-151
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• 2022

This study analyzes patents related to oil diagnosis of construction equipment. Oil diagnosis is extremely important for maintaining construction equipment properly. Through the evaluation of existing patents, a patent strategy for the future construction equipment market is presented. The related patents are classified and selected in several steps. Finally, 16 valid patents are selected and analyzed in detail. In the classification process, patents are classified by country, year, and company. A market analysis shows that the top 10 companies have a market share of more than 50. In addition to patents related to the oil analysis of construction equipment, patents related to automobile oil analysis and development of oil sensors are investigated to identify the contents of patents in other fields that can be applied to oil diagnosis technology for construction equipment. Moreover, not only the contents of research articles of two Korean construction companies, but also the research trends in the literature in this field are used in the analysis. The related patents of the two Korean companies are few. Companies with a high market share, including Caterpillar, hold many patents, and patents for diagnosis algorithms using such technologies as artificial intelligence and artificial neural networks, along with oil sensor-based condition monitoring technology, are gradually expanding.

• The Transactions of the Korean Institute of Electrical Engineers C
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• v.54 no.12
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• pp.546-552
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• 2005

In this paper, a present condition with gas-in-oil diagnosis which used to condition analysis for oil insulated transformer is investigated and reason why hydrogen used to basic diagnosis for the transformer is described. This paper gives an overview of background knowledge that should to consider as moisture detecting of oil immersed paper and how could we approach to life expectancy of oil insulated transformer through detecting furfural compound.

• Journal of the Korean Institute of Intelligent Systems
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• v.19 no.5
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• pp.706-712
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• 2009

In this paper, a fault diagnosis method is proposed to detect and classifies faults that occur in press process line. An oil level automatic monitoring method is also presented to detect oil level. The FFT(fast fourier transform) frequency analysis and ART2 NN(adaptive resonance theory 2 neural network) with uneven vigilance parameters are used to achieve fault diagnosis in proposing method, and GUI(graphical user interface) program for fault diagnosis and oil level automatic monitoring using LabVIEW is produced and fault diagnosis was done. The experiment results demonstrate the effectiveness of the proposed fault diagnosis method of induction motors and oil level automatic monitor system.

• The Transactions of the Korean Institute of Electrical Engineers C
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• v.53 no.10
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• pp.523-529
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• 2004

Faults of cellulosic insulations greatly affect the life span of oil immersed transformers because their performance recovery is impossible. Therefore, the reliable diagnosis technologies are needed for detection of the faults. Dissolved gas analysis technologies using CO and $CO_2$ gases have been widely used for fault diagnosis of cellulosic insulations. In this research, we described Degradation diagnosis of insulation paper CO and $CO_2$ gases in oil immersed Transformers using. We considered the distribution characteristics of CO, $CO_2$ gases' concentrations and ratios of $CO_2$/CO not only in serviced transformers but in experiments with typical fault causes such as heat, partial discharge and moisture. As result, the reliability of diagnosis results for the cellulosic insulations can be improved when the concentrations of CO, $CO_2$ and the ratio of CO/$CO_2$ satisfy each diagnosis criterion at a tim

• Proceedings of the Korean Institute of IIIuminating and Electrical Installation Engineers Conference
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• 1989.10a
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• pp.65-70
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• 1989

This paper presents resarch results on the use of a corona detector and a pulse counter in order to diagnose for oil transformers. Using these experimental apparatus, tests were carried out on a typical transformer oil containing different carbonized paper and various moisture contents to measure the picocoulomb val-ues and pulse count. Through the result of this study it was found that the picocoulomb values and pulse count of corona were depended on the getting stained in transformer oil. The amplitude of the partial discharge amount and the number of pulse were decreased up to 70 [。c] and then was increased as the oil temperature goes up. It was concluded that the determinati-on level for diagnosis of oil transform-er was taken into account the temperatu-er of transformer oil, The use of pulse counter method, which have been taken the same property of voltage and temperature variation for the corona measurement mothod, considera-bly increase insulator avilability.

• Proceedings of the KIEE Conference
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• 1998.07c
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• pp.1079-1081
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• 1998

This paper describes the dissipation factor measuring device for insulating oil in operating pole transformer by DSP(digital signal processor). After applying voltage to the sensor which is installed in a transformer, acquire source voltage and current of sensor using FFT techniques, then we could evaluate the dissipation factor of insulating oil. To improve measuring accuracy and processing speed, we use TMS320C31 DSP, FFT and data analysis techniques. Also we suggest deterioration criterion of insulating oil and compared the developed diagnosis device with schering bridge on deteriorated insulating oil. The result of this paper show that the developed measuring device can be used as diagnosis device for the pole transformers.

• Journal of Electrical Engineering and Technology
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• v.12 no.2
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• pp.830-839
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• 2017

Support vector machine (SVM) is introduced as an effective fault diagnosis technique based on dissolved gases analysis (DGA) for oil-immersed transformers with maximum generalization ability; however, the applicability of the SVM is highly affected due to the difficulty of selecting the SVM parameters appropriately. Therefore, a novel approach combing SVM with improved imperialist competitive algorithm (IICA) for fault diagnosis of oil-immersed transformers was proposed in the paper. The improved ICA, which is proved to be an effective optimization approach, is employed to optimize the parameters of SVM. Cross validation and normalizations were applied in the training processes of SVM and the trained SVM model with the optimized parameters was established for fault diagnosis of oil-immersed transformers. Three classification benchmark sets were studied based on particle swarm optimization SVM (PSOSVM) and IICASVM with four multiple classification schemes to select the best scheme for transformer fault diagnosis. The results show that the proposed model can obtain higher diagnosis accuracy than other methods. The comparisons confirm that the proposed model is an effective approach for classification problems.

• Proceedings of the Korean Institute of IIIuminating and Electrical Installation Engineers Conference
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• 2004.11a
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• pp.87-90
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• 2004

This paper describes development of power transformer maintenance system using intelligent dissolved gases in oil analysis. The used gases are acetylene(C2H2), hydrogen(H2), ethylene(C2H4), methane(CH4), ethane(C2H6), carbon monoxide(CO) and carbon dioxide(CO2). The rule and neural network based gas analysis methods are used for artificial intelligent diagnosis. It is indicated that this program is efficient for diagnosis of oil immersed transformers diagnosis from application of gas analysis data of serviced transformer which has local overheating

• Proceedings of the KIEE Conference
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• 2009.07a
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• pp.2061_2062
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• 2009

Within serviced period of time in transformer, thermal stress is the most influential parameter affecting the aging behavior of an insulation system. The thermal stress on the insulation system may occur from operation in a high temperature environment due to Joule's heat at winding coils. This paper describes a development of capacitive sensor and preventive diagnosis techniques for electrical insulating oil, widely used for power and distribution transformer. To survey the dielectric properties of the virgin and used mineral insulating oil, we utilized the highly precise measuring system of KRISS. And the results were used to determine the design factors of the sensor. To evaluate diagnosis by the sensor, we performed accelerated aging test about insulating oils. The condition of aged specimens were investigated by measurements of relative permittivity i.e. capacitance change by capacitive sensor.

• Proceedings of the KIEE Conference
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• 2000.07a
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• pp.547-549
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• 2000

This paper develops phase sensitive detector for diagnosis of distribution transformers. And to detect the $tan{\delta}$ more effectively, this paper used phase sensitive detector. The sensor in oil which could be placed inside of the distribution transformer can measures the $tan{\delta}$ in oil. This could be the important factor and information, and it could be used for the basic information for a precise diagnosis. Establishment of the proposed system helps to build the confidence in monitoring of the oil-filled transformers.