• Title/Summary/Keyword: Diagnosis Method

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Partial Discharge Position Tracking Method using a GIS Partial Discharge Signal and Arrival Time Difference (GIS 부분방전 신호와 도착 시간차 분석을 통한 PD발생 위치 추적)

  • Choi, Mun-Gyu;Cha, Hanju
    • The Transactions of The Korean Institute of Electrical Engineers
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    • v.62 no.9
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    • pp.1297-1301
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    • 2013
  • This paper analyzes of PD occurrence position through an analysis of the arrival time difference between the GIS partial discharge signal. Because of GIS (Gas Insulated Switchgear) is a facility very important power equipment and as part of the equipment that make up the power system, the stabilization of the power industry, which accounted for 88.5% share of GIS substation in the form of a substation is an important equipment for power supply. In the situation where we are gradually expanding the need for preventive diagnosis in order to improve the efficiency of equipment management and failure prevention for Preventive diagnosis. In this paper as a method for extracting pre-defect of failure of GIS Apply the average value method of calculating the 5 times each using a pulse of the first time of the second pulse (${\Delta}t$) with an oscilloscope generation position PD(Partial Discharge). the results of GIS internal inspection, the partial discharge of the actual the position of the partial discharge was confirmed with an accuracy of about 82% of positions. Arrival time difference in the most effective manner if the partial discharge of GIS internal occurs by applying the averaging method and TOA(Time of arrival) method, the partial discharge occurs you through the measurement and analysis of PD signal occurs was confirmed in the experiment are presented and diagnostic methods location tracking.

A Diagnosis Method of Basal Cell Carcinoma by Raman Spectra of Skin Tissue using NMF Algorithm (피부 조직의 라만 스펙트럼에서 NMF 알고리즘을 통한 기저 세포암 진단 방법)

  • Park, Aaron;Baek, Sung-June
    • Journal of the Institute of Electronics and Information Engineers
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    • v.50 no.8
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    • pp.196-202
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    • 2013
  • Basal cell carcinoma (BCC) is the most common skin cancer and its incidence is increasing rapidly. In this paper, we propose a diagnosis method of basal cell carcinoma by Raman spectra of skin tissue using the NMF(non-negative matrix factorization) algorithm. After preprocessing steps, measured Raman spectra is used classification experiments. The weight and the basis can be obtained in a simple matrix operation and a column vector of the matrix decompsed by the NMF. Linear combination of bases and weights, it is possible to approximate the average of Raman spectra. The classification method is to select the class which to minimize the root mean square of the difference of the linear combination and the objective spectrum. According to the experimental results, the proposed method shows the promising results to diagnosis BCC. In addition, it confirmed that the proposed method compared with the previous research result could be effectively applied in the analysis of the Raman spectra.

Cause Diagnosis Method of Semiconductor Defects using Block-based Clustering and Histogram x2 Distance (블록 기반 클러스터링과 히스토그램 카이 제곱 거리를 이용한 반도체 결함 원인 진단 기법)

  • Lee, Young-Joo;Lee, Jeong-Jin
    • Journal of Korea Multimedia Society
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    • v.15 no.9
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    • pp.1149-1155
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    • 2012
  • In this paper, we propose cause diagnosis method of semiconductor defects from semiconductor industrial images. Our method constructs feature database (DB) of defect images. Then, defect and input images are subdivided by uniform block. And the block similarity is measured using histogram kai-square distance after color histogram calculation. Then, searched blocks in each image are merged into connected objects using clustering. Finally, the most similar defect image from feature DB is searched with the defect cause by measuring cluster similarity based on features of each cluster. Our method was validated by calculating the search accuracy of n output images having high similarity. With n = 1, 2, 3, the search accuracy was measured to be 100% regardless of defect categories. Our method could be used for the industrial applications.

Switch Open Fault Diagnosis of Inverter Using Features of dq Currents (dq 전류의 특징을 이용한 인버터의 스위치 개방 고장진단)

  • Kwak, Nae-Joung;Hwang, Jae-Ho;Hong, Won-Pyo
    • Journal of the Institute of Electronics Engineers of Korea SC
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    • v.48 no.1
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    • pp.31-38
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    • 2011
  • Faults of motor drive systems to be used for various industrial applications can cause serious problems. In this paper, a method to diagnose switch open fault of a voltage-fed PWM inverter is proposed. The proposed method normalizes dq current and fault-detection and first classification are performed by mean values of dq phase currents, second classification is performed by features such as the relation of dq phase currents, the ranges of those, the positions of those according to the results, and fault switch is diagnosed with the results. The proposed method performs the simulation for diagnosis of inverter switch open faults with MATLAB and identifies the feasibility of the proposed method. Because the proposed method is implemented by simple algorithms, the proposed algorithm can be embedded in general induction motor drive systems and be used.

Knee Articular Cartilage Segmentation with Priors Based On Gaussian Kernel Level Set Algorithm (사전정보를 이용한 가우시안 커널 레벨 셋 알고리즘 기반 무릎 관절 연골 자기공명영상 분할기법)

  • Ahn, Chunsoo;Bui, Toan;Lee, Yong-Woo;Shin, Jitae
    • The Journal of Korean Institute of Communications and Information Sciences
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    • v.39C no.6
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    • pp.490-496
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    • 2014
  • The thickness of knee joint cartilage causes most diseases of knee. Therefore, an articular cartilage segmentation of knee magnetic resonance imaging (MRI) is required to diagnose a knee diagnosis correctly. In particular, fully automatic segmentation method of knee joint cartilage enables an effective diagnosis of knee disease. In this paper, we analyze a well-known level-set based segmentation method in brain MRI, and apply that method to knee MRI with solving some problems from different image characteristics. The proposed method, a fully automatic segmentation in whole process, enables to process faster than previous semi-automatic segmentation methods. Also it can make a three-dimension visualization which provides a specialist with an assistance for the diagnosis of knee disease. In addition, the proposed method provides more accurate results than the existing methods of articular cartilage segmentation in knee MRI through experiments.

Application of Hot Start PCR Method in PCR-based Preimplantation Genetic Diagnosis

  • Kim, Sung-Ah;Kang, Moon-Joo;Kim, Hee-Sun;Oh, Sun-Kyung;Ku, Seung-Yup;Choi, Young-Min;Jun, Jong-Kwan;Moon, Shin-Yong
    • Journal of Genetic Medicine
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    • v.9 no.1
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    • pp.11-16
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    • 2012
  • Purpose: To determine a method to improve the efficacy and accuracy of preimplantation genetic diagnosis (PGD) - polymerase chain reaction (PCR), we compared hot start PCR and conventional multiplex nested PCR. Materials and Methods: This study was performed with single lymphocyte isolated from whole blood samples that were obtained from two couples with osteogenesis imperfecta (OI). We proceeded with conventional multiplex nested PCR and hot start PCR in which essential reaction components were physically removed, and we compared the amplification rate, allele dropout rate and nonspecific products. Afterward, we used selective method for PGD. Results: In the two couples, the respective amplification rate were 93.5% and 80.0% using conventional multiplex nested PCR and 95.5% and 92.0% using hot start PCR. The respective mean allele dropout rates for the two couples were 42.0% and 14.0% with conventional multiplex nested PCR and 36.0% and 6.0% with hot start PCR. Conclusion: The results demonstrate that the hot start PCR procedure provides higher amplification rates and lower allele dropout rate than the conventional method and that it decreased the nonspecific band in multiplex nested PCR. The hot start method is more efficient for analyzing a single blastomere in clinical PGD.

A Study on the Improvement of Repair and Reinforcement Quantity Take-off in Fire-damaged Area Using 3D Laser Scanning (3D Laser Scanning을 활용한 화재 손상 부위의 보수·보강 물량 산출 방식 개선에 관한 연구)

  • Jeong, Hoi-Jae;Ham, Nam-Hyuk;Lee, Byoung-Do;Park, Kwang-Min;Kim, Jae-Jun
    • Journal of KIBIM
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    • v.9 no.1
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    • pp.11-21
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    • 2019
  • Recently, there is an increase in fire incidents in building structures. Due to this, the importance of fire-damaged buildings' safety diagnosis and evaluation after fire is growing. However, the existing fire-damaged safety diagnosis and evaluation methods are personnel-oriented, so the diagnostic results are intervened by investigators' subjectivity and unquantified. Thus, improper repair and reinforcement can result in secondary damage accidents and economic losses. In order to overcome these limitations, this study proposes using 3D laser scanning technology. The case analysis of fire-damaged building structures was conducted to verify the effectiveness of accuracy and manpowering by comparing the existing method and the proposed method. The proposed method using 3D laser scanning technology to obtain point cloud data of fire-damaged field. The point cloud data and BIM model is combined to inspect the fire-damaged area and depth. From inspection, quantified repair and reinforcement quantity take-off can be acquired. Also, the proposed method saves half of the manpowering within same time period compared to the existing method. Therefore, it seems that using 3D laser scanning technology in fire-damaged safety diagnosis and evaluation will improve in accuracy and saving time and manpowering.

Analysis of Medical Images Using EM-based Relationship Method (EM기반 관계기법을 이용한 의료영상 분석)

  • Kim, Hyung-Il
    • Journal of the Korea Society of Computer and Information
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    • v.14 no.12
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    • pp.191-199
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    • 2009
  • The integrated medical information system is an effective medical diagnosis assistance system which offers an environment in which medial images and diagnosis information can be shared. Because of the large-scale medical institutions and their cooperating organizations are operating the integrated medical information systems, they can share medical images and diagnosis information. However, this system can only stored and transmitted information without other functions. To resolve this problem and to enhance the efficiency of diagnostic activities, a medical image analysis system is necessary. In this paper, the proposed relationship method analyzes medical images for features generation. Under this method, the medical images have been segmented into several objects. The medical image features have been extracted from each segmented image. Then, extracted features were applied to the Relationship Method for medical image analysis. Several experimental results that show the effectiveness of the proposed method are also presented.

Development of an Automatic Comprehensive Condition Diagnosis System for Inductive Loop Detector Using Magnetic Field (자기장을 이용한 루프검지기 자동진단시스템 개발)

  • Kim, Nam-Sun;Lee, Seung-Hwan;Oh, Young-Tae;Lee, Choul-Ki;Kang, Jeung-Sik
    • Journal of Korean Society of Transportation
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    • v.23 no.5 s.83
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    • pp.123-134
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    • 2005
  • This research aims at developing a new method which can replace the existing method. known as the quality factor(Q factor) method by an L-R-C test for use in the performance test of inductive loop detectors(ILD) being installed and maintained. In this study, a sensor to detect a magnetic field in terms of frequency and intensity, a method to collect field data, the method of analysis, and the method of diagnosis were developed. An automatic diagnosis system which was developed to overcome those drawbacks has the following features : First, field data is collected automatically by a test vehicle equipped with magnetic field sensors that is running can be said to along the roadway and. thus, the new system completely overcome the roadway and, thus, the new system can be said to completely overcome the inefficiency of the existing method second, since the magnetic fold generated from the ILD is the final output of the whole system of ILD, the existing problem has been solved. third. since each of the detection area by height is collected by the magnetic sensors installed by height. a basic for the identification of the vehicle types to be detectable and the setting of adjustment factors has been made. For the automatic diagnosis system developed during in this study, a reliability test was carried out by comparing vehicle times of ILD installed ideally.