• Title/Summary/Keyword: Main diagnosis

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Study on an Intelligent Ferrography Diagnosis Expert System

  • Jiadao, Wang;Darong, Chen;Xianmei, Kong
    • Proceedings of the Korean Society of Tribologists and Lubrication Engineers Conference
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    • 2002.10b
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    • pp.455-456
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    • 2002
  • Wear is one of the main factors causing breakdown and fault of machine, so ferrography technique analyzing wear particles can be an effective way for condition monitoring and fault diagnosis. On the base of the forward multilayer neural network, a nodes self-deleting neural network model is provided in this paper. This network can itself deletes the nodes to optimize its construction. On the basis of the nodes self-deleting neural network, an intelligent ferrography diagnosis expert system (IFDES) for wear particles recognition and wear diagnosis is described. This intelligent expert system can automatically slim lip knowledge by learning from samples and realize basically the entirely automatic processing from wear particles recognition to wear diagnosis.

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A Fault Detection and Diagnosis in a PWR Steam Generator (PWM 증기발생기의 고장검출 및 진단에 관한 연구)

  • Park, Seung-Yub
    • The Transactions of the Korean Institute of Electrical Engineers
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    • v.40 no.1
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    • pp.120-127
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    • 1991
  • The purpose of this study is to develop a fault detection and diagnosis scheme that can monitor process fault and instrument fault of a steam generator. The suggested scheme consists of a Kalman filter and two bias estimators. Method of detecting process and instrument fault in a steam generator uses the mean test on the residual sequence of Kalman filter, designed for the unfailed system, to make a fault decision. Once a fault is detected, two bias estimators are driven to estimate the fault and to discriminate process fault and instrument fault. In case of process fault, the fault diagnosis of outlet temperature, feed-water heater and main steam control value is considered. In instrument fault, the fault diagnosis of steam genrator's three instruments is considered. Computer simulation tests show that on-line prompt fault detection and diagnosis can be performed very successfully.

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Image recognition technology in rotating machinery fault diagnosis based on artificial immune

  • Zhu, Dachang;Feng, Yanping;Chen, Qiang;Cai, Jinbao
    • Smart Structures and Systems
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    • v.6 no.4
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    • pp.389-403
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    • 2010
  • By using image recognition technology, this paper presents a new fault diagnosis method for rotating machinery with artificial immune algorithm. This method focuses on the vibration state parameter image. The main contribution of this paper is as follows: firstly, 3-D spectrum is created with raw vibrating signals. Secondly, feature information in the state parameter image of rotating machinery is extracted by using Wavelet Packet transformation. Finally, artificial immune algorithm is adopted to diagnose rotating machinery fault. On the modeling of 600MW turbine experimental bench, rotor's normal rate, fault of unbalance, misalignment and bearing pedestal looseness are being examined. It's demonstrated from the diagnosis example of rotating machinery that the proposed method can improve the accuracy rate and diagnosis system robust quality effectively.

Study on Visible Diagnosis of Appearnce (망형태(望形態)에 대한 연구)

  • Kim Yong-Chan;Kang Jung-Soo
    • Journal of Physiology & Pathology in Korean Medicine
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    • v.19 no.6
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    • pp.1483-1490
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    • 2005
  • This study was written in order to help understanding of visible diagnosis of appearance(形). Visible diagnosis of appearance(形) is a very important factor of diagnosis and a first step of visible diagnosis. appearance(形) is closely connection with spirit(神), so is house of spirit(神). If we make a visible diagnosis of appearance(形), we know the prosperousness of energy and the relative seriousness of an illness. Spirit(神) is understood by appearances and movements of patient, and influenced by seasons, lands, human's relationship and the grade of age. By visible diagnosis of appearance(形), we can conclude existence or nonexistence of spirit(神), As comparing spirit(神) with appearance(形), we can decide good or bad prognoses. One man's own appearance(形) is determined by the five human type(五形人). There are very various points of changing form. As divided into principal groups, there are three main groups, that is, sky(天), earth(地) and man(人). The age and sex belong 治 the factor of sky(天), a direction and configuration of the ground(地形) belong to the factor of earth(地), the five human type(五形人) and white fatness(肥白) and black emaciation(黑瘦) belong to the factor of man(人).

Machine's Determination of Main Color and Imbalance in a Drawing for Art Psychotherapy (그림진단을 위한 주제색 및 불균형 판단의 자동화)

  • Bae Jun;Kim Jae Min;Kim Seong-in
    • Journal of Institute of Control, Robotics and Systems
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    • v.12 no.2
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    • pp.119-129
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    • 2006
  • Art psychotherapy is widely accepted as an effective tool for diagnosis and treatment of psychological disorders. Important factors for art psychotherapy diagnosis, based on the projection theory that the world of the inner mind appears in drawings, include main color and imbalance of a drawing. This paper develops a system for a machine to determine the main color and the imbalance of a drawing by color recognition and edge detection. Our proposed color recognition procedure adopts NBS(National Bureau of Standards) distance between colors in HVC(Hue, Value, Chroma) color space which is most similar to the human eye's color perception. Our edge detection procedure applies blurring, clustering and transformation to a standard color in a series. Our system considers the numbers of pixels and clusters for each color as a criterion for main color and the frequency of edge coordinates for each region for imbalance. The proposed machine procedure, verified through case studies, can help overcome the subjectivity, ambiguity and uncertainty in human decision involved in art psychotherapy.

Researches Trend of Korea Institute of Oriental Medicine in Sasang Constitution Field - from 2007 to 2010 (한국한의학연구원의 사상체질 연구동향 - 2007년부터 2010년까지의 논문을 중심으로 -)

  • Lee, Young-Seop;Kim, Sang-Hyuk;Lee, Si-Woo
    • Korean Journal of Oriental Medicine
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    • v.18 no.1
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    • pp.59-74
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    • 2012
  • Objective : The aim of this study is to investigate current status of Sasang constitutional medicine researches and to provide source in setting a development strategy and making a policy on the Sasang constitutional medicine. Method : This study analyzed trends in research as represented in the 142 articles of Korea Institute of Oriental Medicine in the field of Sasang constitution medicine from 2007 to 2010. Result : The main themes of studies were Sasang constitution clinical study (68, 47%) and developing instruments for measuring diagnosis (48, 33%), especially pulse diagnosis (25, 17%). Genetic researches and trends studies on Sasang constitutional medicine were respectively 17 (12%) and 8 (5%). As a result, Korea Institute of Oriental Medicine established Sasang clinical information bank, and discovered clinical character of Sasang constitution to develope various diagnosis tools include constitution survey form and pulse diagnosis instrument. Genetic researches also discover constitution related genes such as FTO and MC4R, and explore association between heredity and Sasang constitution. Conclusion : The above mentioned achievements of Korea Institute of Oriental Medicine were limited to diagnosis process, unquestionably studies for reproducibility and authenticity of constitution diagnosis were important mission of Sasang constitutional medicine. However, to develop the advance of Sasang constitutional medicine, not only constitution diagnosis but also constitutional treatment studies should be conducted.

Tongue Image Segmentation Using CNN and Various Image Augmentation Techniques (콘볼루션 신경망(CNN)과 다양한 이미지 증강기법을 이용한 혀 영역 분할)

  • Ahn, Ilkoo;Bae, Kwang-Ho;Lee, Siwoo
    • Journal of Biomedical Engineering Research
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    • v.42 no.5
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    • pp.201-210
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    • 2021
  • In Korean medicine, tongue diagnosis is one of the important diagnostic methods for diagnosing abnormalities in the body. Representative features that are used in the tongue diagnosis include color, shape, texture, cracks, and tooth marks. When diagnosing a patient through these features, the diagnosis criteria may be different for each oriental medical doctor, and even the same person may have different diagnosis results depending on time and work environment. In order to overcome this problem, recent studies to automate and standardize tongue diagnosis using machine learning are continuing and the basic process of such a machine learning-based tongue diagnosis system is tongue segmentation. In this paper, image data is augmented based on the main tongue features, and backbones of various famous deep learning architecture models are used for automatic tongue segmentation. The experimental results show that the proposed augmentation technique improves the accuracy of tongue segmentation, and that automatic tongue segmentation can be performed with a high accuracy of 99.12%.

Statistical Techniques based Computer-aided Diagnosis (CAD) using Texture Feature Analysis: Applied of Cerebral Infarction in Computed Tomography (CT) Images

  • Lee, Jaeseung;Im, Inchul;Yu, Yunsik;Park, Hyonghu;Kwak, Byungjoon
    • Biomedical Science Letters
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    • v.18 no.4
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    • pp.399-405
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    • 2012
  • The brain is the body's most organized and controlled organ, and it governs various psychological and mental functions. A brain abnormality could greatly affect one's physical and mental abilities, and consequently one's social life. Brain disorders can be broadly categorized into three main afflictions: stroke, brain tumor, and dementia. Among these, stroke is a common disease that occurs owing to a disorder in blood flow, and it is accompanied by a sudden loss of consciousness and motor paralysis. The main types of strokes are infarction and hemorrhage. The exact diagnosis and early treatment of an infarction are very important for the patient's prognosis and for the determination of the treatment direction. In this study, texture features were analyzed in order to develop a prototype auto-diagnostic system for infarction using computer auto-diagnostic software. The analysis results indicate that of the six parameters measured, the average brightness, average contrast, flatness, and uniformity show a high cognition rate whereas the degree of skewness and entropy show a low cognition rate. On the basis of these results, it was suggested that a digital CT image obtained using the computer auto-diagnostic software can be used to provide valuable information for general CT image auto-detection and diagnosis for pre-reading. This system is highly advantageous because it can achieve early diagnosis of the disease and it can be used as supplementary data in image reading. Further, it is expected to enable accurate medical image detection and reduced diagnostic time in final-reading.

Analysis of breakdown on the Main-Transfomer tertiary cable (주변압기 3차케이블 고장원인분석사례)

  • Park, Min-Goo;Jin, Seung-Whan;Won, Gyeong-Bae;Cho, Chong-Eun
    • Proceedings of the KIEE Conference
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    • 2015.07a
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    • pp.1488-1489
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    • 2015
  • 본 논문에서는 154kV 주변압기 3차측에서 사용하고 있는 6~10kV급 전력케이블인 TFR-CV $400mm^2$의 절연파괴고장에 대한 원인을 분석하였다. 대상 케이블은 2010년 9월에 가압하여 약 4.4년 운전 후 발생하였으며 차폐부 제거 후 열수축튜브를 시공한 사례이다. 위와 같이 차폐부를 제거한 케이블의 고장분석사례를 소개하고 고장 재발방지방안을 제안하고자 한다. 이 논문은 향후 변압기 신 증설 및 교체, 운영에 활용할 수 있을 것으로 사료된다.

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A Study on Analysis of Defects cause for Rotor in the High Voltage Induction Motors (고압유도전동기의 회전자 결함요인 분석에 관한 연구)

  • Lee, Eun-Chun;Byun, Doo-gyoon;Chae, Ji-Seog;Byun, Ill-Hwan
    • Proceedings of the KIEE Conference
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    • 2015.07a
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    • pp.655-656
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    • 2015
  • In this paper, diagnosis for 85 high voltage induction motors which have operated for more than 20 years in 18 wide area water supply offices were applied and the results of diagnosis were analysed. Furthermore, main factors that would be affecting rotor defects were selected and correlations between dependent variables which was magnitude for sideband frequency on current during operation and independent variables such as starting characteristic, operating time, number of operation, load factor, maker, rotation speed, capacity were analysed. It was clear that factors including starting characteristic, number of operation, maker, rotation speed caused break by correlation analysis. From this, regression equation was deduced through regression analysis. Based on suggested regression equation, it is applied usefully that we can estimate the condition of rotor without onsite diagnosis and plan the schedule of diagnosis.

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