• Proceedings of the KIEE Conference
• /
• 2006.07e
• /
• pp.45-46
• /
• 2006

변압기 내부의 수분은 절연물의 절연내력에 악영향을 끼치므로 수분측정은 변압기 사고예방과 수명연장에 매우 중요하다. 변압기 내의 수분함유량을 검출하는 시험법으로 Karl-Fischer법과 Dew-Point법을 사용해 왔다. 그러나 이 시험법은 기기를 분해해야 하고, 국부적인 부분에 대한 정보일 뿐 아니라 분석을 즉시 현장에서 하지 못하는 단점이 있다. 따라서 기존 시험법의 단점을 보완하기 위해 회복전압법(RVM, Return Voltage Method)이 제안되었다. 본 논문에서는 모의 셀 내부에 수분을 강제로 주입하여 수분함유량 변화를 주고 Karl-Fischer법을 통한 수분함유량 측정 결과와 RVM 특성 곡선을 비교 분석하였다.

• Journal of the Korean Society of Systems Engineering
• /
• v.14 no.2
• /
• pp.16-23
• /
• 2018

The intended system's function and performance can be assured through implementing the development process, the verification compliance against corresponding requirements, in accordance with the fundamental principle from the Systems Engineering. For the effective verification implementation, related core metadata should be selected and managed throughout the development life cycle. And these have to be included in the configuration document such as specification so that taking them as development baselines each phases if necessary. In this paper, associated case study results are introduced to establish the Requirements Verification Matrix (RVM) for the verification management on the space launch vehicle development program.

• Journal of Power Electronics
• /
• v.16 no.3
• /
• pp.1097-1109
• /
• 2016

Fault detection and isolation are related to system monitoring, identifying when a fault has occurred, and determining the type of fault and its location. Fault detection is utilized to determine whether a problem has occurred within a certain channel or area of operation. Fault detection and diagnosis have become increasingly important for many technical processes in the development of safe and efficient advanced systems for supervision. This paper presents an integrated technique for fault diagnosis and classification for open- and short-circuit faults in three-phase inverter circuits. Discrete wavelet transform and principal component analysis are utilized to detect the discontinuity in currents caused by a fault. The features of fault diagnosis are then extracted. A fault dictionary is used to acquire details about transistor faults and the corresponding fault identification. Fault classification is performed with a fuzzy logic system and relevance vector machine (RVM). The proposed model is incorporated with a set of optimization techniques, namely, evolutionary particle swarm optimization (EPSO) and cuckoo search optimization (CSO), to improve fault detection. The combination of optimization techniques with classification techniques is analyzed. Experimental results confirm that the combination of CSO with RVM yields better results than the combinations of CSO with fuzzy logic system, EPSO with RVM, and EPSO with fuzzy logic system.

• Journal of the Korea Academia-Industrial cooperation Society
• /
• v.14 no.1
• /
• pp.385-392
• /
• 2013

A key element of the fog warning system to prevent large traffic accidents is a visibility measurement device. Recently, the need for it that is similar to the human visual sense and cheap and accurate than expensive fog sensors is increasing. In this paper, we present the performance evaluation and the economic analysis of the Road Visibility Measurement System (RVMS), which is developed for measuring the road visibility through a CCTV camera. For experiments, we have installed a CCTV camera, a fog sensor, and visibility signs at the Yeo-ju Test Road on the Central Inland Expressway. We evaluated the measurements from RVMS and the fog sensor based on observations. The result shows RVMS outperforms the fog sensor with respect to measurement stability and correctness. We also show RVMS has higher economic feasibility and various applications. RVMS can prevent the traffic accidents caused by severe fog and enhance the process of the wide-area visibility information system significantly.

• 한국HCI학회:학술대회논문집
• /
• 2008.02a
• /
• pp.569-572
• /
• 2008

The possibility to extent the solution in human detection problem for plug-in on vision-based Human Computer Interaction domain is very attractive, since the successful of the machine leaning theory and computer vision marriage. Bayesian logistic regression is a powerful classifier performing sparseness and high accuracy. The difficulties of finding people in an image will be conquered by implementing this Bavesian model as classifier. The comparison with other massive classifier e.g. SVM and RVM will introduce acceptance of this method for human detection problem. Our experimental results show the good performance of Bavesian logistic regression in human detection problem, both in trade-off curves (ROC, DET) and real-implementation compare to SVM and RVM.

• International Journal of Fuzzy Logic and Intelligent Systems
• /
• v.16 no.3
• /
• pp.157-162
• /
• 2016

In this paper, a yield prediction model based on relevance vector machine (RVM) and a granular computing model (quotient space theory) is presented. With a granular computing model, massive and complex meteorological data can be analyzed at different layers of different grain sizes, and new meteorological feature data sets can be formed in this way. In order to forecast the crop yield, a grey model is introduced to label the training sample data sets, which also can be used for computing the tendency yield. An RVM algorithm is introduced as the classification model for meteorological data mining. Experiments on data sets from the real world using this model show an advantage in terms of yield prediction compared with other models.

• Transactions of the Korean Society of Automotive Engineers
• /
• v.4 no.3
• /
• pp.130-138
• /
• 1996

The transient incompressible flow behind the widely-spaced co-axial jet is numerically simulated using the random vortex method(RVM). This numerical approach is based on the Lagrangian approach for the vorticity formulation of the unsteady Navier-Stokes equations, utilizing vortex elements to account for the convection and diffusion processes. The effects of the mass flow rate of an annular air jet and a central fuel jet on the co-axial jet flow dynamics is investigated. To validate the present procedure, the numerical results are compared with the available experimental data the present procedure, the numerical results are compared with the available experimental data in terms of the centerline and off-centerline profiles of the mean axial velocity. Discrepancies between the RVM results and the measurements are discussed in detail.

• Proceedings of the Korean Institute of Electrical and Electronic Material Engineers Conference
• /
• 2004.07a
• /
• pp.499-502
• /
• 2004

In order to detect of insulation problems an early, transformer has to be performed the several tests. The ac current and tan6 of transformer winding insulation were investigated by Schering bridge. Partial discharge(PD) tests are used to evaluate the insulation condition of transformer. The moisture content measurement was conducted using RVM(recovery voltage meter). The RVM test can show that the problem is affecting the paper insulation of transformer. The value of moisture content was 2.3% in main transformer. The insulations of four transformers were judged to be in good condition.

• Proceedings of the KIEE Conference
• /
• 2007.04b
• /
• pp.43-45
• /
• 2007

최근 국내에는 변압기의 사용이 급속도로 증가하고 있지만 신뢰도가 높은 진단이 어려워 26년의 기준수명보다 오래 사용하지 못하고 폐기하는 상황이다. 본 논문에서는 변압기사고 및 수명단축의 가장 큰 원인인 수분의 분포특성을 확인해 보았다. 현재 수분을 측정하는 방법에는 Dew-Point법, Karl- Fisher법, RVM등 여러 가지가 있는데 Karl-Fisher법과 RVM를 사용하여 샘플채취 위치에 대한 특성을 실험하였다.

• Geomechanics and Engineering
• /
• v.15 no.6
• /
• pp.1207-1217
• /
• 2018

Geomechanics parameters are critical to numerical simulation, stability analysis, design and construction of geotechnical engineering. Due to the limitations of laboratory and in situ experiments, back analysis is widely used in geomechancis and geotechnical engineering. In this study, a hybrid back analysis method, that coupling numerical simulation, response surface (RS) and relevance vector machine (RVM), was proposed and applied to identify geomechanics parameters from hydraulic fracturing. RVM was adapted to approximate complex functional relationships between geomechanics parameters and borehole pressure through coupling with response surface method and numerical method. Artificial bee colony (ABC) algorithm was used to search the geomechanics parameters as optimal method in back analysis. The proposed method was verified by a numerical example. Based on the geomechanics parameters identified by hybrid back analysis, the computed borehole pressure agreed closely with the monitored borehole pressure. It showed that RVM presented well the relationship between geomechanics parameters and borehole pressure, and the proposed method can characterized the geomechanics parameters reasonably. Further, the parameters of hybrid back analysis were analyzed and discussed. It showed that the hybrid back analysis is feasible, effective, robust and has a good global searching performance. The proposed method provides a significant way to identify geomechanics parameters from hydraulic fracturing.