• Journal of Power Electronics
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• 제16권5호
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• pp.1981-1989
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• 2016

Battery diagnosis is vital to battery-based applications because it ensures system reliability by avoiding battery failure. This paper presents a novel intelligent battery charger with an online diagnosis function to circumvent interruptions in system operation. The charger operates in normal charging and diagnosing modes. The diagnosis function is performed with the impedance spectroscopy technique, which is achieved by injecting a sinusoidal voltage excitation signal to the battery terminals without the need for additional hardware. The impedance spectrum of the battery is calculated based on voltage excitation and current response with the aid of an embedded digital lock in amplifier in a digital signal processor. The measured impedance data are utilized in the application of the complex nonlinear least squares method to extract the battery parameters of the equivalent circuit. These parameters are then compared with the reference values to reach a diagnosis. A prototype of the proposed charger is applied to four valve-regulated lead-acid batteries to measure AC impedance. The results are discussed.

• 한국소음진동공학회논문집
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• 제16권1호
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• pp.27-33
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• 2006

Fault diagnosis and condition monitoring for rotating machines are important for efficiency and accident prevention. The process of fault diagnosis is to extract the feature of signals and to classify each state. Conventionally, fault diagnosis has been developed by combining signal processing techniques for spectral analysis and pattern recognition, however these methods are not able to diagnose correctly for certain rotating machines and some faulty phenomena. In this paper, we add a minimum detection error algorithm to the previous method to reduce detection error rate. Vibration signals of the induction motor are measured and divided into subband signals. Each subband signal is processed to obtain the RMS, standard deviation and the statistic data for constructing the feature extraction vectors. We make a study of the fault diagnosis system that the feature extraction vectors are applied to K-means clustering algorithm and minimum detection error algorithm.

• 정보처리학회논문지B
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• 제16B권2호
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• pp.165-172
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• 2009

최근 ACS에 따르면 여성에게 유방암은 가장 많이 발병하는 암으로서 그 사망자 수도 두 번째로 많은 암이다. 유방 X선 영상의 종괴나 석회 환부는 진단을 위한 가장 중요한 단서로서 알려져 있으므로 유방암의 조기진단을 위하여 디지털 유방 X선 영상을 컴퓨터에서 처리하는 연구가 진행되고 있다. 본 논문에서는 퍼지 클러스터 지식베이스에 기반을 둔 진단시스템을 제안한다. 제안된 시스템은 듀얼 OFUN-NET에 두 가지 종류의 특징 데이터를 처리하여 진단결과와 그 가능성을 알려준다. 실세계 의료기관으로부터 수집되고 공개적으로 제공되는 유방 X선 데이터베이스 DDSM으로부터 획득한 종괴와 석회 환부의 데이터를 사용하여 실험한다. 실험결과는 제안된 시스템이 기존의 방법보다 높은 분류 정확도와 유방 X선 영상 진단시스템으로서 전문가의 의사 결정을 도울 수 있는 타당한 결과를 보여준다.

• Nuclear Engineering and Technology
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• 제50권8호
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• pp.1306-1313
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• 2018

The randomness and incipient nature of certain faults in reactor systems warrant a robust and dynamic detection mechanism. Existing models and methods for fault diagnosis using different mathematical/statistical inferences lack incipient and novel faults detection capability. To this end, we propose a fault diagnosis method that utilizes the flexibility of data-driven Support Vector Machine (SVM) for component-level fault diagnosis. The technique integrates separately-built, separately-trained, specialized SVM modules capable of component-level fault diagnosis into a coherent intelligent system, with each SVM module monitoring sub-units of the reactor coolant system. To evaluate the model, marginal faults selected from the failure mode and effect analysis (FMEA) are simulated in the steam generator and pressure boundary of the Chinese CNP300 PWR (Qinshan I NPP) reactor coolant system, using a best-estimate thermal-hydraulic code, RELAP5/SCDAP Mod4.0. Multiclass SVM model is trained with component level parameters that represent the steady state and selected faults in the components. For optimization purposes, we considered and compared the performances of different multiclass models in MATLAB, using different coding matrices, as well as different kernel functions on the representative data derived from the simulation of Qinshan I NPP. An optimum predictive model - the Error Correcting Output Code (ECOC) with TenaryComplete coding matrix - was obtained from experiments, and utilized to diagnose the incipient faults. Some of the important diagnostic results and heuristic model evaluation methods are presented in this paper.

• 한국컴퓨터정보학회논문지
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• 제26권2호
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• pp.39-44
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• 2021

본 논문에서는 가정에서 많이 기르는 반려견을 바탕으로 반려견 질병에 대한 전문적인 수의학 지식이 부족한 일반인들을 대상으로 자신의 반련견의 건강 상태를 파악할 수 있는 진단 시스템을 제안한다. 제안된 진단 시스템은 50가지 질병과 각 질병의 증상을 데이터베이스에 구축하여 입력된 증상을 통해서 반려견의 질병을 도출한다. 각 질병 데이터베이스에는 질병에 해당하는 증상 코드들을 가지고 있으며, 이러한 질병에 대한 데이터베이스를 이용하여 군집화 기법인 FCM 클러스터링 기법을 적용하여 질병을 클러스터링하고 그 결과 값인 소속도를 바탕으로 입력된 증상과 가까운 질병들을 도출하여 반려견의 진단 결과를 제공한다. 제안된 반려견 진단의 구현 결과에서는 선택한 증상들의 개수와 선택된 증상들이 포함된 질병들의 가능성 값을 구하여 내림차순으로 정렬하여 반려견의 증상과 가장 가까운 질병 상위 3가지를 도출하였다.

• 터널과지하공간
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• 제19권1호
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• pp.19-30
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• 2009

비파괴 물리탐사 방법의 일종인 충격반향법 조사는 터널 구조물의 시공 중 품질관리 및 시공 후 구조물의 건전성을 파악하기 위한 안전진단 분야에 널리 사용되고 있다. 충격반향법은 특히 철근콘크리트로 시공된 라이닝에 대하여 라이닝의 두께나 터널 배면 공동 등 내부 상태를 파악하는데 가장 효과적인 비 파괴탐사 방법이다. 본 연구는 현장적용 사례 연구의 일환으로 철근 콘크리트 라이닝의 도로터널, NATM공법으로 시공된 지하철 터널, 재래식 공법으로 시공된 도로터널 등 구조 및 형식이 다른 여러 가지 터널에 대하여 충격반향법 조사를 실시하였다. 충격반향법 탐사 결과를 기존 설계도서, 코어링 자료 및 다른 탐사자료와 대비하였을 때 서로 잘 일치하였고 충격반향법 탐사결과의 신뢰도를 확인할 수 있었으며, 시간-주파수 분석은 구조물 내부 특성에 대한 추정을 보다 용이하게 하였다. 1차원적인 한 지점에서의 수직하부 정보를 구하는 통상적인 주파수 영역에서의 충격반향법 자료해석과 더불어 2차원적인 심도단면도를 구하는 탐사법 적용은 구조물을 보다 정확하게 영상화할 수 있기 때문에 구조물 내부에 대한 신뢰도 높은 정보 파악이 가능하였다.

• 대한한의학원전학회지
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• 제33권1호
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• pp.89-101
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• 2020

Objectives : The purpose of this study is to research the Left-Renying and Right-Qikou pulse diagnosis. Methods : We set up locations of the Renying pulse(人迎脈) and the Qikou pulse(氣口脈) on left hand and right hand. On the basis of the medical texts and papers, we researched the relations between the Left-Renying and Right-Qikou pulse diagnosis and the etiological factors(病因), background of appearance of the Left-Renying and Right-Qikou pulse diagnosis, and practical use of medical practitioners of many generations to the Left-Renying and Right-Qikou pulse diagnosis. Results & Conclusions : The Left-Renying and Right-Qikou pulse diagnosis is a method to diagnosis the etiological factors, while it could also be assumed as a tool to apply herbal medicine. This assumption could be made based on the seventh volume of 『Maijing(脈經)』 of Wang Shuhe(王叔和). Chen Wuze(陳無擇) emphasized its function to distinguish etiological factors in 『Sanyinjiyibingzhengfanglun(三因極一病證方論)』, as did Li Dongyuan(李東垣) in 『Neiwaishangbianhuolun(內外傷辨惑論)』. Meanwhile, the connection between Left-Renying and Right-Qikou pulse diagnosis and Zangfu(臟腑) seems to have first been made in 『Maiyu(脈語)』 of Wu Kun(吳昆), while 『Zhenjiazhengyan(診家正眼)』 of Li Zhongzi(李中梓) shows traces of progress since the 『Maiyu』.

• 한국추진공학회:학술대회논문집
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• 한국추진공학회 2008년 영문 학술대회
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• pp.16-21
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• 2008

Aero-engine, as one kind of rotating machinery with complex structure and high rotating speed, has complicated vibration faults. Therefore, condition monitoring and fault diagnosis system is very important for airplane security. In this paper, a vibration data acquisition and intelligent fault diagnosis system is introduced. First, the vibration data acquisition part is described in detail. This part consists of hardware acquisition modules and software analysis modules which can realize real-time data acquisition and analysis, off-line data analysis, trend analysis, fault simulation and graphical result display. The acquisition vibration data are prepared for the following intelligent fault diagnosis. Secondly, two advanced artificial intelligent(AI) methods, mapping-based and rule-based, are discussed. One is artificial neural network(ANN) which is an ideal tool for aero-engine fault diagnosis and has strong ability to learn complex nonlinear functions. The other is data mining, another AI method, has advantages of discovering knowledge from massive data and automatically extracting diagnostic rules. Thirdly, lots of historical data are used for training the ANN and extracting rules by data mining. Then, real-time data are input into the trained ANN for mapping-based fault diagnosis. At the same time, extracted rules are revised by expert experience and used for rule-based fault diagnosis. From the results of the experiments, the conclusion is obvious that both the two AI methods are effective on aero-engine vibration fault diagnosis, while each of them has its individual quality. The whole system can be developed in local vibration monitoring and real-time fault diagnosis for aero-engine.

• Journal of Acupuncture Research
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• 제21권1호
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• pp.1-20
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• 2004

Pulse-feeling took its origin from making a diagnosis along meridians in the course of discovering and forming meridians and for a long time its meaning was mixed with meridians in the course of recognizing "The Pulse" then was separated from meridians in the early days of Western Han Dynasty. Ancient pulse-feeling methods are pulse-feeling method by the twelve regular meridians, pulse-feeling method by three regions and nine modes, pulse-feeling method by Inyeong(人迎) and Chon-gu(寸口), etc. Pulse-feeling was changed in proportion to diagnostic purpose and method of treating and if method and region of pulse-feeling is arranged, we will infer correlation between meridians and pulse-feeling and will infer transitional system of past pulse-feeling and will forecast transition of future pulse-feeling. As the result that I study the transition of the above three pulse-feeling methods of meridians diagnosis: 1. Three pulse-feeling methods of meridians diagnosis flowed into diagnostic method by taking pulse of setting six region for Chon(寸), Gwan(關) and Cheok(尺), i.e. the Chon[寸] spot pulse of $\ll$Nan-gyeong$\gg$ and were changed into diagnostic method being fit for use of five Su points, The Front-Mo points and Back-Su points that grasp the pathology of mutual internal organs and treat the disease. 2. Today it is suggesting the transition of another pulse-feeling method that do not apply diagnostic method by taking pulse of setting six region for Chon(寸), Gwan(關) and Cheok(尺), i.e. the Chon[寸] spot pulse of $\ll$Nan-gyeong$\gg$ to 19C Sasang(四象) Constitutional Medicine or 20C Eight Constitutional Medicine.

• 대한한의학원전학회지
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• 제29권3호
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• pp.113-132
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• 2016

Objectives : In this study, the Abdominal Diagnostic Method of Kitao Shunpo(北尾春圃) about Movement Qi between kidneys in Sanghauidam(桑韓醫談) and Jeonggisinron(精氣神論) are investigated for the purpose of understanding the definite technique of the method and the position in the context of abdominal diagnosis in Japan. Methods : The materials related to the abdominal diagnosis to Movement Qi between kidneys were selected from Sanghauidam and Jeonggisinron written by Kitao Shunpo, and analyzed to know the characteristics of the method. Results : Kitao Shunpo suggested the theoretical background of the Abdominal Diagnostic Method that Original Qi(元氣) is made from Original Essence(元精) when a person is born, and mentality(神) and body essence(精), qi(氣) and blood(血) are formed from those. Movement Qi between kidneys(腎間動氣), that is to say innate Original Qi can be diagnosed in abdominal region by the method in Japanese Medicine. Kitao Shunpo decided deficiency and excess of Original Qi and prognosis in clinical treatment by the method, and suggested the standard pulse condition of the Movement Qi between kidneys. Conclusions : After the theory about Movement Qi between kidneys appeared in Nanjing(難經), many doctors have not made attention to diagnose that for a long time, until Kitao Shunpo with other Japanese doctors established the theoretical background of the Abdominal Diagnostic Method, and applied the theory to clinical treatment.