• 제목/요약/키워드: MIMS

검색결과 16건 처리시간 0.021초

부분방전 패턴인식을 위해 EMC센서를 이용한 최적화된 RBFNNs 분류기 설계 (Design of Optimized Radial Basis Function Neural Networks Classifier Using EMC Sensor for Partial Discharge Pattern Recognition)

  • 정병진;이승철;오성권
    • 전기학회논문지
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    • 제66권9호
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    • pp.1392-1401
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    • 2017
  • In this study, the design methodology of pattern classification is introduced for avoiding faults through partial discharge occurring in the power facilities and local sites. In order to classify some partial discharge types according to the characteristics of each feature, the model is constructed by using the Radial Basis Function Neural Networks(RBFNNs) and Particle Swarm Optimization(PSO). In the input layer of the RBFNNs, the feature vector is searched and the dimension is reduced through Principal Component Analysis(PCA) and PSO. In the hidden layer, the fuzzy coefficients of the fuzzy clustering method(FCM) are tuned using PSO. Raw datasets for partial discharge are obtained through the Motor Insulation Monitoring System(MIMS) instrument using an Epoxy Mica Coupling(EMC) sensor. The preprocessed datasets for partial discharge are acquired through the Phase Resolved Partial Discharge Analysis(PRPDA) preprocessing algorithm to obtain partial discharge types such as void, corona, surface, and slot discharges. Also, when the amplitude size is considered as two types of both the maximum value and the average value in the process for extracting the preprocessed datasets, two different kinds of feature datasets are produced. In this study, the classification ratio between the proposed RBFNNs model and other classifiers is shown by using the two different kinds of feature datasets, and also we demonstrate the proposed model shows superiority from the viewpoint of classification performance.

12채널 Multi-frequency를 이용한 경혈 임피던스 측정시스템 개발 및 평가 (Development & Evaluation of acupuncture Point Impedance Measurement System Using 12 Channels Multi-Frequency)

  • 김수병;이재우;이승욱;이나라;김영대;신태민;이용흠
    • Korean Journal of Acupuncture
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    • 제28권1호
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    • pp.1-13
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    • 2011
  • Objectives : The object of this study is to evaluate and develop the system that reflects acupoints electrical properties by the multi-frequency using the SPAC (Single Power Alternative Current) stimulation method based on BIA (Bioelectrical impedance method). Methods : The 12 channel meridian impedance measurement system (MIMS) was designed, which sets multi-frequency with 10 steps (1~10kHz). To check acupoints electrical properties, impedance of acupoints were measured from 11 acupoints selected from the LU and ST meridians. Results : Regarding distribution of measurement values by multi-frequencies, we found the lowest response at 1kHz was in common. But frequency bands which represent the highest response at each acupoint were various. Measurement values of each acupoint by multi-frequencies were expressed similar distribution (P<0.05). Also we could check same frequency band which showed the highest response at left/right equal acupoints (P<0.05). Conclusions : Through change of acupoints electrical properties by multi-frequency stimulation, we checked oriental medical diagnostic possibilities by using this system. We would progress variable clinical trials with this system for oriental medical diagnosis.

Korea Emissions Inventory Processing Using the US EPA's SMOKE System

  • Kim, Soon-Tae;Moon, Nan-Kyoung;Byun, Dae-Won W.
    • Asian Journal of Atmospheric Environment
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    • 제2권1호
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    • pp.34-46
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    • 2008
  • Emissions inputs for use in air quality modeling of Korea were generated with the emissions inventory data from the National Institute of Environmental Research (NIER), maintained under the Clean Air Policy Support System (CAPSS) database. Source Classification Codes (SCC) in the Korea emissions inventory were adapted to use with the U.S. EPA's Sparse Matrix Operator Kernel Emissions (SMOKE) by finding the best-matching SMOKE default SCCs for the chemical speciation and temporal allocation. A set of 19 surrogate spatial allocation factors for South Korea were developed utilizing the Multi-scale Integrated Modeling System (MIMS) Spatial Allocator and Korean GIS databases. The mobile and area source emissions data, after temporal allocation, show typical sinusoidal diurnal variations with high peaks during daytime, while point source emissions show weak diurnal variations. The model-ready emissions are speciated for the carbon bond version 4 (CB-4) chemical mechanism. Volatile organic carbon (VOC) emissions from painting related industries in area source category significantly contribute to TOL (Toluene) and XYL (Xylene) emissions. ETH (Ethylene) emissions are largely contributed from point industrial incineration facilities and various mobile sources. On the other hand, a large portion of OLE (Olefin) emissions are speciated from mobile sources in addition to those contributed by the polypropylene industry in point source. It was found that FORM (Formaldehyde) is mostly emitted from petroleum industry and heavy duty diesel vehicles. Chemical speciation of PM2.5 emissions shows that PEC (primary fine elemental carbon) and POA (primary fine organic aerosol) are the most abundant species from diesel and gasoline vehicles. To reduce uncertainties in processing the Korea emission inventory due to the mapping of Korean SCCs to those of U.S., it would be practical to develop and use domestic source profiles for the top 10 SCCs for area and point sources and top 5 SCCs for on-road mobile sources when VOC emissions from the sources are more than 90% of the total.

국방 정보자원관리를 위한 핵심아키텍처데이터모델 개발 기법 (A Development Technique of Core Architecture Data Model(CADM) for Defense Information Resource Management)

  • 최남용;진종현;송영재
    • 정보처리학회논문지D
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    • 제11D권3호
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    • pp.683-690
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    • 2004
  • 현대 국방부에서는 국방정보체제간의 상호운용성을 보장하기 위해 아키텍처 산출물을 쉽고 일관성 있게 개발할 수 있는 국방아키텍처프레임워크를 개발하고 있다. 따라서, 개발된 아키텍처 산출물을 저장하여 재사용하고 국방 전반의 아키텍처 정보의 교환, 비교, 통합을 용이하게 하는 핵심아키텍처데이터모델(CADM)의 개발이 필요하다. CADM은 국방아키택처프레임워크에서 도출된 데이터 요구사항을 통해 엔티터를 추출하여 관계를 정의하였으며 실사례를 통해 엔티티를 검증하였다. 설사례로는 군사정보통합처리체계의 아키텍처 산출물을 작성하여 그들의 아키텍처 데이터를 저장소에 저장한 후 다양한 쿼리를 통해 검증하였다. CADM을 통해 전군의 아키텍처에 대한 공통의 데이터 모델을 제공하여 국방정보체계에 대한 통합적인 정보자원관리와 상호운용 및 통합을 향상시킬 수 있다.

K-means 클러스터링 기반 소프트맥스 신경회로망 부분방전 패턴분류의 설계 : 분류기 구조의 비교연구 및 해석 (Design of Partial Discharge Pattern Classifier of Softmax Neural Networks Based on K-means Clustering : Comparative Studies and Analysis of Classifier Architecture)

  • 정병진;오성권
    • 전기학회논문지
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    • 제67권1호
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    • pp.114-123
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    • 2018
  • This paper concerns a design and learning method of softmax function neural networks based on K-means clustering. The partial discharge data Information is preliminarily processed through simulation using an Epoxy Mica Coupling sensor and an internal Phase Resolved Partial Discharge Analysis algorithm. The obtained information is processed according to the characteristics of the pattern using a Motor Insulation Monitoring System program. At this time, the processed data are total 4 types that void discharge, corona discharge, surface discharge and slot discharge. The partial discharge data with high dimensional input variables are secondarily processed by principal component analysis method and reduced with keeping the characteristics of pattern as low dimensional input variables. And therefore, the pattern classifier processing speed exhibits improved effects. In addition, in the process of extracting the partial discharge data through the MIMS program, the magnitude of amplitude is divided into the maximum value and the average value, and two pattern characteristics are set and compared and analyzed. In the first half of the proposed partial discharge pattern classifier, the input and hidden layers are classified by using the K-means clustering method and the output of the hidden layer is obtained. In the latter part, the cross entropy error function is used for parameter learning between the hidden layer and the output layer. The final output layer is output as a normalized probability value between 0 and 1 using the softmax function. The advantage of using the softmax function is that it allows access and application of multiple class problems and stochastic interpretation. First of all, there is an advantage that one output value affects the remaining output value and its accompanying learning is accelerated. Also, to solve the overfitting problem, L2-normalization is applied. To prove the superiority of the proposed pattern classifier, we compare and analyze the classification rate with conventional radial basis function neural networks.

IoT를 이용한 지하매설물관리용 지능형표지기(IMI) 기술개발에 관한 연구 (A Study on the Development of Intelligent Markup Indicator (IMI) Technology for Underground Facilities Management Using IoT)

  • 김태달
    • 한국인터넷방송통신학회논문지
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    • 제17권3호
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    • pp.129-136
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    • 2017
  • 과거 지리정보시스템 GIS(Geographic Information System)의 활용영역이 정부와 몇몇 공공분야에 국한돼 있었으나, 최근 모바일, CRM(Customer Relationship Management) 등 다른 영역과 결합하면서 시장이 다양해지고 있다. 21세기 GIS기술의 발전방향은 GIS응용시스템 개발 및 공간정보 서비스를 위한 제반 기술로서 웹 GIS, 3차원 GIS, 모바일 GIS, LBS 등을 들 수 있다. 본 연구에서는 기존에 사용하고 있는 지하매설물 관련 표지못의 단순 위치파악 기능에서 탈피해서 새로운 개념의 표지못(지능형 저장 메모리장치를 내장한 표지못)을 개발해서, 현장에서 지하매설물관련 정보 (설치일자, 매설 깊이, 배관 두께, 배관 재질, 관리기관, 시공자, 연락처 등)를 입력하고 DB서버에 저장해서, 필요하면 적시. 적소에서 활용할 수 있게 한다. 본 연구를 통해 무분별한 굴착기 공사 등으로 야기되는 각종 사고를 미리 방지하고, 최소화 할 수 있으며, 싱크홀 관련 대책 수립을 위한 정보제공 등. 지하매설물관리를 체계적이며, 신뢰성 있는 정보 제공이 가능하도록, 현장에서 편리하게 정보를 입력할 방안을 제시함으로써, 지하 매설관로 사고를 절대적으로 감소시킬 수 있도록 하는 목적을 두고 연구 개발하였다.