• Proceedings of the KIEE Conference
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• 2007.04b
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• pp.166-168
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• 2007

The DGA (Dissolved Gases Analysis) technique has been widely using for fault diagnosis of the power transformers. This technique has a high reliability than other techniques. KEPCO (Korea Electric Power Cooperation) has been using DGA technique since KEPCO established the criteria of DGA in 1985. In this paper, we introduce the DGA criteria of KEPCO and analyze the result of DGA. Also we introduce the cases of thoroughgoing inspection of the power transformers caused by DGA and compare the judgment of DGA with the result of throughgoing inspection.

• Proceedings of the KIEE Conference
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• 2007.07a
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• pp.95-96
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• 2007

Dissolved gas analysis (DGA) is one of the most widely used diagnostic tools for detecting and evaluating faults in electrical equipment. However, interpretation of DGA results is often complex and should always be done with care, involving experienced insulation maintenance personnel. KEPCO (Korea Electric Power Cooperation) has been using DGA technique since KEPCO established the criteria of DGA in 1985. In this paper, we introduce the DGA criteria of KEPCO and analyze the result of DGA. Also we sort pattern in result of DGA. Then, relation between pattern and inner inspection was studied. 67 DGA data was used for analyzing pattern. Some patterns have something to do with cause of incipient fault.

• Convergence Security Journal
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• v.22 no.5
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• pp.145-154
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• 2022

Recently, the widespread proliferation and high sophistication of botnets are having serious consequences not only for enterprises and users, but also for cyber warfare between countries. Therefore, research to detect botnets is steadily progressing. However, the DGA-based botnet has a high detection rate with the existing signature and statistics-based technology, but also has a high limit in the false positive rate. Therefore, in this paper, we propose a detection model using text-based n-gram to detect DGA-based botnets. Through the proposed model, the detection rate, which is the limit of the existing detection technology, can be increased and the false positive rate can also be minimized. Through experiments on large-scale domain datasets and normal domains used in various DGA botnets, it was confirmed that the performance was superior to that of the existing model. It was confirmed that the false positive rate of the proposed model is less than 2 to 4%, and the overall detection accuracy and F1 score are both 97.5%. As such, it is expected that the detection and response capabilities of DGA-based botnets will be improved through the model proposed in this paper.

• Journal of Electrical Engineering and Technology
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• v.9 no.2
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• pp.615-621
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• 2014

Power transformer is one of the most important equipments in electrical power system. The detection of certain gases generated in transformer is the first indication of a malfunction that may lead to failure if not detected. Dissolved gas analysis (DGA) of transformer oil has been one of the most reliable techniques to detect the incipient faults. Many conventional DGA methods have been developed to interpret DGA results obtained from gas chromatography. Although these methods are widely used in the world, they sometimes fail to diagnose, especially when DGA results falls outside conventional method codes or when more than one fault exist in transformer. To overcome these limitations, fuzzy inference system (FIS) is proposed. 250 different cases are used to test the accuracy of various DGA methods in interpreting the transformer condition.

• Journal of IKEEE
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• v.24 no.1
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• pp.354-359
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• 2020

DGA(Dissolved Gas Analysis) is regularly performed to detect internal defects of power transformers and prevent failures. The overheating or discharging in the transformer can be confirmed by DGA but the defective parts should be identified by internal inspection. However, winding or iron core defects cannot be checked by internal inspection, so it is impossible to establish actions by DGA alone. In this paper, the internal defect mode is analyzed and presented based on the transformer internal inspection reports, and the internal defect can be predicted by considering DGA.

• Proceedings of the KIEE Conference
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• 2006.11a
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• pp.141-143
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• 2006

Dissolved gas analysis (DGA) is widely used to detect incipient faults in oil-filled electrical equipment. KEPCO make a rule of DGA in 1985. They have been diagnosing power transformer using their DGA criteria. In this paper, we analysis the result of DGA data about transformer in the substation. We try to find out what is cause of an error in DGA diagnosis considering accuracy in extracting gases from mineral oil in transformer. The carbon-monoxide was primary reason of warning in DGA data. We specially consider that aging is a cause of generating of carbon-monoxide in power transformer.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.56 no.12
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• pp.2084-2090
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• 2007

The DGA (Dissolved Gases Analysis) technique has been widely using for fault diagnosis of the power transformers. Some electric power utility company establishes the criteria of DGA to improve reliability, because of difference of operation environment and design of power transformer. In this paper, we introduce intelligent diagnosis system for DGA result of KEPCO (Korea Electric Power Cooperation). This system can classify patterns type of gases ratio that frequently occurs in recent result of gases analysis using Fuzzy Inference. The classification of Patterns let us know that major causes of gases generation based on type of patterns. Finally, Neural Network based on patterns diagnose transformer. NN was trained using result data of DGA of actually faulted transformers recently. Result of intelligent diagnosis system is right well in comparison with actual inner inspection of transformers.

• Journal of Acupuncture Research
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• v.19 no.3
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• pp.107-114
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• 2002

Objective : This study was designed to find the most effective and safest way to overcome Lumbago due to blood stasis and sprain involved in a few Meridian Tendino-musculatures by evaluating the effect of two kinds of Dong-gi(Dong-qi) Acupuncture(DGA) and by reporting their side effects. Material : 97 patients of out and admission patients were selected, who were diagnosed with lumbar sprain caused by repetitive bending, heavy weight lifting, unsuitable posture, concussion and falling down and whose Lumbago due to blood stasis and sprain in the concept of oriental medicine. Methods : 97 patients were divided into three groups. One is exclusive DGA group to which DGA and the method retaining needles on the acupoints for about 20 minutes were applied, the other is DGA combined active exercise group in which patients stretched their Meridian Tendino-muscuIatures with their hips moving up and downward repeatedly during DGA, the third is DGA combined passive exercise group in which patients were made to flex or extend their bodies on the auto flexion-distraction table in a prone position, from 10 to 20 degree, during DGA. In each group, bed rest, physical therapy and herbal medicine were used according to symptoms, in addition to DGA. In DGA method, "Su(Shu)" points of the meridian related to the involved Meridian Tendino-musculature were mainly chosen, that is, Sokkol(Shugu, B65), Hugye(Houxi, SI3), ChungJo(Zhongzhu, TE3) were used, for most LBP belonged to Bladder and Gallbladder Meridian Tendino-musculature disorders. Pyong-Bo-Pyong-Sa(Ping-Bu-Ping-Xie) such as Dong-Gi and Yeom-Jeon(Nian-Zhuan) was applied as Bo-Sa method. For evaluation of effectiveness, new score system was devised by severity of pain and range of movement. the score was given twice at patients' first and last visit and the difference between first and last score was regarded as a evaluation scale, the effectiveness was classified into four grade by evaluation scale.(scale : 12-15; excellent, 8-11; good, 4-7; fair, 0-3; bad) Results : 1. Exclusive DGA, DGA combined active exercise and DGA combined passive exercise group showed 97, 87 and 89% in effectiveness. 2. Exclusive DGA, DGA combined active exercise and DGA combined passive exercise group showed no aggravation of pain, range of movement. 3. In blood test of 34 patients, only one patient showed abnormal rise of sGOT, sGPT and $\gamma$-GTP at his first visit and the others didn't show any detrimental change. DGA had no bad influence upon BUN and creatinine of patients. Conclusion : For complex theraphy combining DGA, exercise, physical therapy and Herbal medicine proved to be highly effective on treating lumbago due to blood stasis and sprain, this is expected to be available for clinical use.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.28 no.5
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• pp.1141-1151
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• 2018

In an APT attack, the communication stage between infected hosts and C&C(Command and Control) server is the key stage for intrusion into the attack target. Attackers can control multiple infected hosts by the C&C Server and direct intrusion and exploitation. If the C&C Server is exposed at this stage, the attack will fail. Therefore, in recent years, the Domain Generation Algorithm (DGA) has replaced DNS in C&C Server with a short time interval for making detection difficult. In particular, it is very difficult to verify and detect all the newly registered DNS more than 5 million times a day. To solve these problems, this paper proposes a model to judge DGA-DNS detection by the morphological similarity analysis of normal DNS and DGA-DNS, and to determine the sign of APT attack through it, then we verify its validity.

• Korean Journal of Artificial Intelligence
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• v.5 no.1
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• pp.18-28
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• 2017

Recently, there are many companies that use systems based on artificial intelligence. The accuracy of artificial intelligence depends on the amount of learning data and the appropriate algorithm. However, it is not easy to obtain learning data with a large number of entity. Less data set have large generalization errors due to overfitting. In order to minimize this generalization error, this study proposed DGA which can expect relatively high accuracy even though data with a less data set is applied to machine learning based genetic algorithm to deep learning based dropout. The idea of this paper is to determine the active state of the nodes. Using Gradient about loss function, A new fitness function is defined. Proposed Algorithm DGA is supplementing stochastic inconsistency about Dropout. Also DGA solved problem by the complexity of the fitness function and expression range of the model about Genetic Algorithm As a result of experiments using MNIST data proposed algorithm accuracy is 75.3%. Using only Dropout algorithm accuracy is 41.4%. It is shown that DGA is better than using only dropout.