• Journal of Power Electronics
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• v.16 no.5
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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.

• Transactions of the Korean Society for Noise and Vibration Engineering
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• v.16 no.1 s.106
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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.

• The KIPS Transactions:PartB
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• v.16B no.2
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• pp.165-172
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• 2009

According to the American Cancer Society, breast cancer is the second largest cause of cancer deaths and most frequently diagnosed cancer in women. The currently most popular method for early detection of breast cancer is the digital mammography. A mass or calcification lesion has been known as the most important clue for the diagnosis. In this paper, we propose a diagnosis approach based on fuzzy cluster knowledge base. We combine different two sources of feature data in duel OFUN-NET and produce the diagnosis result with possibility degree. We also present the experimental results on the dataset of mass and calcification lesions extracted from the public real world mammogram database DDSM. These results show higher classification accuracy than conventional methods and the feasibility as a decision supporting tool for diagnosis of digital mammogram.

• Nuclear Engineering and Technology
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• v.50 no.8
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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.

• Journal of the Korea Society of Computer and Information
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• v.26 no.2
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• pp.39-44
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• 2021

In this paper, we propose a method of disease diagnosis system that can diagnose the health status of household pets for the people who lack veterinary knowledge. The proposed diagnosis system holds 50 different kinds of diseases with the symptoms for each of them as a database to provide results from symptom input. Each disease database has its own symptom codes for a disease, and by using the disease database, FCM clustering technique is applied to disease which outputs membership degree to determine diseases close to the input symptom as a pet diagnosis result. The implementation results of the proposed pet diagnosis system were obtained by the number of selected symptoms and the possibility values of the diseases that have the selected symptoms being sorted in descending order to derive top 3 diseases closest to the pet's symptom.

• Tunnel and Underground Space
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• v.19 no.1
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• pp.19-30
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• 2009

For the purpose of determining the thickness of concrete lining and detect of the cavity where may be located behind tunnel lining, IE (Impact-Echo) method it effectively useful in the tunnel safety diagnosis and the quality control during the construction. As a part of case study, we applied IE method to various tunnel structure types such as road tunnel and subway tunnel constructed by NATM (New Austrian Tunnelling Method) and ASSM (American Steel Support Method). As tunnel specifications estimated from this method were compared with coring data, design drawing and other survey results, it was very good agreement with each other. In conclusion, we verified that IE method shows an accurate and reliable result. The conventional interpretation of IE method in frequency domain gives only vertical information at a certain point. However, the interpretation using time-frequency analysis and depth section imaging technique from two dimensional profiling surveys can show more reliable information about structure inside.

• Journal of Korean Medical classics
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• v.33 no.1
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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』.

• Proceedings of the Korean Society of Propulsion Engineers Conference
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• 2008.03a
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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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• v.21 no.1
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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.

• Journal of Korean Medical classics
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• v.29 no.3
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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.